{"as_of":"2026-08-10T17:06:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3885aeb07ea5e8dc0eef9aab0457fef8d657b78d21afae22b29b11f9f8e43568","coverage":[{"denominator":63,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":63,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T11:50:01.382249Z","state":"measured"},{"denominator":63,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":63,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.29200/citation-record","integrity":"/paper/2607.29200/integrity","json":"/paper/2607.29200/citation-record.json","paper":"/paper/2607.29200"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:54.657797Z","title":"U-net: Convolutional networks for biomedical image segmentation","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:54.657797Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:acde6f5ef482b319970ec179a2e148ab0f1187062b714d1cea7ab5a779adbbf5","observation_id":"7be83830-0c7a-4357-9ba2-a942af52a9d0","resolution":{"observed_at":"2026-08-03T11:49:54.657797Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:54.712015Z","title":"nnu-net: a self-configuring method for deep learning-based biomedical image segmentation.Nature methods, 18(2):203–211, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:54.712015Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:d5388b661c3a5febaf50dc2546c53dd9c4d21f364386085a80dace487dc3f38b","observation_id":"b51f43e2-d244-4092-a8a6-1da7df94c149","resolution":{"observed_at":"2026-08-03T11:49:54.712015Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2102.04306","last_updated":"2021-02-08T16:10:50Z","snapshot_observed_at":"2026-08-10T02:39:10.770770Z","submitted_at":"2021-02-08T16:10:50Z","title":"TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.04306","snapshot_observed_at":"2026-08-03T11:49:54.816080Z","title":"Transunet: Transformers make strong encoders for medical image segmentation.arXiv preprint arXiv:2102.04306, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:54.816080Z"},"links":{"cited_paper":"/paper/2102.04306","citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:61b803b7d71a4f0e75a2449ab6f5489cc7040e17da6f4ff5b97e53038596d575","observation_id":"dbd46e4a-dbf6-4795-98aa-0a0207fade7c","resolution":{"observed_at":"2026-08-03T11:49:54.816080Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:54.972335Z","title":"Unetr: Transformers for 3d medical image segmentation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:54.972335Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:3d45cd49b77f55d0c4ce14320acd6411236b82bcaf588f6aad059e2f5fae3187","observation_id":"ea80fa4e-9771-4983-835b-b1280661c8c8","resolution":{"observed_at":"2026-08-03T11:49:54.972335Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.04722","last_updated":"2024-01-09T18:53:20Z","snapshot_observed_at":"2026-07-06T17:13:25.341853Z","submitted_at":"2024-01-09T18:53:20Z","title":"U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.04722","snapshot_observed_at":"2026-08-03T11:49:55.094182Z","title":"U-mamba: Enhancing long-range dependency for biomedical image segmentation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:55.094182Z"},"links":{"cited_paper":"/paper/2401.04722","citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:b6979ad62e680b10ca1db5ade18aee0dc27089e5ec1cbe6563acc0185feaeadd","observation_id":"9252f68a-3f09-4ce2-a04d-9ea1e5577024","resolution":{"observed_at":"2026-08-03T11:49:55.094182Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:55.195144Z","title":"Vm-unet: Vision mamba unet for medical image segmentation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:55.195144Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:5491f7b3474132ab58cc0bfd4881ceb1bc6fcfbb99a6ad62252ef8a1568217f0","observation_id":"6dff32c4-015f-4dc5-8c46-00a96c64f6c9","resolution":{"observed_at":"2026-08-03T11:49:55.195144Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:55.294583Z","title":"Swin-umamba: Mamba-based unet with imagenet-based pretraining","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:55.294583Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:fa061b6f04deccc2195149dd85ccdbc434f01ce8fa49f1739bc1e9d308f4baaa","observation_id":"fdd45d3a-fa95-403e-8df5-d9aada064818","resolution":{"observed_at":"2026-08-03T11:49:55.294583Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:55.406188Z","title":"Log-vmamba: local-global vision mamba for medical image segmentation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:55.406188Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:255b4c9d52a34fd3f5998f8ce5be9629c41e4ff38bcf3e0ef62725a319ea477b","observation_id":"4ae82ab7-efa6-452d-baa4-951cbc7ad5a3","resolution":{"observed_at":"2026-08-03T11:49:55.406188Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:55.555176Z","title":"Segment anything","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:55.555176Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:f68564fbf1afaae5d1f11afb092cb3784189aa510b8c1d6cf74d29219a1e0ae5","observation_id":"d6614b47-1444-4613-b885-1e0885ecd6c2","resolution":{"observed_at":"2026-08-03T11:49:55.555176Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00714","last_updated":"2024-10-28T16:37:57Z","snapshot_observed_at":"2026-07-06T18:55:41.459417Z","submitted_at":"2024-08-01T17:00:08Z","title":"SAM 2: Segment Anything in Images and Videos","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00714","snapshot_observed_at":"2026-08-03T11:49:55.677692Z","title":"Sam 2: Segment anything in images and videos.arXiv preprint arXiv:2408.00714, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:55.677692Z"},"links":{"cited_paper":"/paper/2408.00714","citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:55b8a7bd289c78817bad4c11413170c4d20b9ef46b09885db50165e7dbe83541","observation_id":"c2198afc-2780-493c-bfae-313b561f663d","resolution":{"observed_at":"2026-08-03T11:49:55.677692Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:55.778442Z","title":"Segment anything in medical images.Nature communications, 15(1):654, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:55.778442Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:d363e254d8ba318ad33005444f8cbc8b799295d12e2a2883aecd8e883527bdd5","observation_id":"52929b92-fae2-4015-8bd3-185bcc36ea96","resolution":{"observed_at":"2026-08-03T11:49:55.778442Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.03600","last_updated":"2025-04-04T17:13:37Z","snapshot_observed_at":"2026-08-08T02:19:23.143138Z","submitted_at":"2025-04-04T17:13:37Z","title":"MedSAM2: Segment Anything in 3D Medical Images and Videos","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.03600","snapshot_observed_at":"2026-08-03T11:49:55.880693Z","title":"Medsam2: Segment anything in 3d medical images and videos.arXiv preprint arXiv:2504.03600, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:55.880693Z"},"links":{"cited_paper":"/paper/2504.03600","citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:ee2efea23c50303352b7d98b9f867d95b2d3ee27f0287852185bb66b48c8c45b","observation_id":"7e68bf7d-3db7-4c17-ba7c-f071f4f76479","resolution":{"observed_at":"2026-08-03T11:49:55.880693Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:55.971293Z","title":"Ultrasam: a foundation model for ultrasound using large open-access segmentation datasets.International Journal of Computer Assisted Radiology and Surgery, pages 1–10, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:55.971293Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:2d177ca2ee489c6e3009aca318d297195c88f02dc6f7eed5e95144f92b086bf6","observation_id":"9c2e5fcc-250d-4f91-87a8-eff2d88086f3","resolution":{"observed_at":"2026-08-03T11:49:55.971293Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:56.079711Z","title":"Samusa: Segment anything model 2 for ultrasound annotation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:56.079711Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:7623d29b06d29f43b8ba15a625f5a8172a1f9fb68e5d0f48fec3bfa6e970a4a5","observation_id":"e84d59c8-f485-49a2-9a85-445c45651a97","resolution":{"observed_at":"2026-08-03T11:49:56.079711Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2511.16719","last_updated":"2026-03-28T16:54:56Z","snapshot_observed_at":"2026-08-07T05:59:39.049027Z","submitted_at":"2025-11-20T18:59:56Z","title":"SAM 3: Segment Anything with Concepts","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.16719","snapshot_observed_at":"2026-08-03T11:49:56.183672Z","title":"Sam 3: Segment anything with concepts.arXiv preprint arXiv:2511.16719, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:56.183672Z"},"links":{"cited_paper":"/paper/2511.16719","citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:84a20e09b38caf769edcfea9bbf05c06df172a7e9409eb9a69262f93a6f2486f","observation_id":"d3ab7f2c-a1e6-459d-99c4-d5a361050aef","resolution":{"observed_at":"2026-08-03T11:49:56.183672Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.12971","last_updated":"2024-06-04T18:16:52Z","snapshot_observed_at":"2026-08-09T23:48:15.002913Z","submitted_at":"2024-05-21T17:54:06Z","title":"BiomedParse: a biomedical foundation model for image parsing of everything everywhere all at once","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.12971","snapshot_observed_at":"2026-08-03T11:49:56.290699Z","title":"Biomedparse: a biomedical foundation model for image parsing of everything everywhere all at once.arXiv preprint arXiv:2405.12971, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:56.290699Z"},"links":{"cited_paper":"/paper/2405.12971","citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:27d14c2d618ec77a7e2e08c457be794ec2a1a93b230c454e39f7eeed80a8c488","observation_id":"72e96467-f585-4da2-adf8-dfb837e6c3ce","resolution":{"observed_at":"2026-08-03T11:49:56.290699Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:56.394603Z","title":"Large-vocabulary segmentation for medical images with text prompts.NPJ Digital Medicine, 8(1):566, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:56.394603Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:23568abfbc5ef070f61620e0aefe83b227f2e890cb4ec542efe467035dc26f8f","observation_id":"69798145-612a-444f-b00b-e4c6b37570aa","resolution":{"observed_at":"2026-08-03T11:49:56.394603Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:56.484662Z","title":"Unibiomed: A universal foundation model for grounded biomedical image interpretation.arXiv preprint arXiv:2504.21336, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:56.484662Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:c3a8bdc6dc9e2d2885552a76e1cb9e755e0dcefce6f2a9be34af86e500e24df3","observation_id":"8f29c071-dcbc-4790-a308-7420f139fa3b","resolution":{"observed_at":"2026-08-03T11:49:56.484662Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:56.737336Z","title":"Medsam3: Delving into segment anything with medical concepts.arXiv preprint arXiv:2511.19046, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:56.737336Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:dd5f728b370b0517fa1307a9d35743e503500a063941f409bfa12ced70508c4c","observation_id":"c0163abe-d1c6-4497-9b7c-343c47f3c0b6","resolution":{"observed_at":"2026-08-03T11:49:56.737336Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:56.964979Z","title":"Medical sam3: A foundation model for universal prompt-driven medical image segmentation.arXiv preprint arXiv:2601.10880, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:56.964979Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:48ee47f2707a342e5807f9b1684d509c4925299b26b579fe7d6c934bc7702533","observation_id":"3ce064fe-de0f-47dd-b1eb-fde0fda2353e","resolution":{"observed_at":"2026-08-03T11:49:56.964979Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:57.114724Z","title":"Kd-eye: Lightweight pupil segmentation for eye tracking on vr headsets via knowledge distillation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:57.114724Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:8fd1fd0b4437b84ddb15f822e4674ea19b4b544354f81663d2d65362fc7fe638","observation_id":"683fac44-7e97-4434-8e97-e1f29ab159ed","resolution":{"observed_at":"2026-08-03T11:49:57.114724Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:57.257958Z","title":"Echogpt: An interactive cardiac function assessment model for echocardiogram videos","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:57.257958Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:24bfa799e7b7e23bcb0a40e01841886947ac388b18e86c2ca5e1cc8dbd658932","observation_id":"ce8b9a41-e243-4c08-af6c-2e301eec2596","resolution":{"observed_at":"2026-08-03T11:49:57.257958Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:57.353129Z","title":"Segment anything model 2: an application to 2d and 3d medical images.IEEE Transactions on Biomedical Engineering, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:57.353129Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:5616f7bf69de16668242e8d321a4bddfe3fa50eed3b95bf513669e7118dd4de1","observation_id":"7c862846-a06e-4820-9e7b-ce930596dd76","resolution":{"observed_at":"2026-08-03T11:49:57.353129Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:57.413131Z","title":"AbdomenUS: US Simulation and Segmentation","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:57.413131Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:02a592b3b924e9193e9954bee17ba7acefca9b069fc22b5a1f2304c5d1c2dd6e","observation_id":"864cf11b-d6d2-4ce5-9680-75333fc58a10","resolution":{"observed_at":"2026-08-03T11:49:57.413131Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:57.462802Z","title":"Bus-bra: A breast ultrasound dataset for assessing computer-aided diagnosis systems.Medical physics, 51(4):3110–3123, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:57.462802Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:a286092c9fe242465d5a3e832a64d42612fbc649969b8d76ec5e708e156e7d55","observation_id":"a499fc60-b9ba-49af-a307-2c523fb301aa","resolution":{"observed_at":"2026-08-03T11:49:57.462802Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:57.546820Z","title":"Video-based ai for beat-to-beat assessment of cardiac function.Nature, 580(7802):252–256, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:57.546820Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:a23d5007e9649722ad3e6a9a6b40558bc239b76b514f11cb77c13cea9916d20f","observation_id":"1481195b-5690-480b-b2c6-98fde628be68","resolution":{"observed_at":"2026-08-03T11:49:57.546820Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:57.627911Z","title":"Mi-segnet: Mutual information-based us segmentation for unseen domain generalization","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:57.627911Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:591ccb773e112786d6f78891cff4476bad99c568858319fa5071d737eb34778f","observation_id":"749586e1-ae2f-4e01-9609-3cc14d8cb31d","resolution":{"observed_at":"2026-08-03T11:49:57.627911Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:57.745435Z","title":"Pubic symphysis-fetal head segmentation and angle of progression, March 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:57.745435Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:2be238c040b3f00d4e5f549aa7c812c7598e84649b910f330a6b679fecb6f8e7","observation_id":"af75d571-448a-46b6-806d-52586ac77408","resolution":{"observed_at":"2026-08-03T11:49:57.745435Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:57.801869Z","title":"Ultrasound Normal Kidney Image Dataset","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:57.801869Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:f09de1b19ecd6b4965e4d216e5e9b3a8a8ad82a8746a932f63df1c03b16706b7","observation_id":"797f18c7-d80d-46cf-9c13-a62ed1915560","resolution":{"observed_at":"2026-08-03T11:49:57.801869Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:57.913953Z","title":"Annotated ultrasound liver images, November 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:57.913953Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:bdcc46d6bf3df8626108525be43099e4ca111c8a59e41b7be92a7b16ce1d9ff6","observation_id":"f8195773-bc5b-483a-990b-3d826835581f","resolution":{"observed_at":"2026-08-03T11:49:57.913953Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:58.000208Z","title":"Lung ultrasound covid phantom dataset used for training machine learning model","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:58.000208Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:92dbca5b75d44511cc69f8a731267f59342ed8101c8654b794e897a4acc83ac7","observation_id":"0ac373ed-8201-4947-9e30-4a17a4f1bfc3","resolution":{"observed_at":"2026-08-03T11:49:58.000208Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:58.057781Z","title":"Deep learning segmentation of transverse musculoskeletal ultrasound images for neuromuscular disease assessment.Computers in biology and medicine, 135:104623, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:58.057781Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:55834606e260a69276318dfc242a92d908a7ebabe7b548e10496fb0b0ba296e9","observation_id":"19fefe49-ab7e-4c0d-8d46-62ae05ea29e3","resolution":{"observed_at":"2026-08-03T11:49:58.057781Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:58.108481Z","title":"Mallesnet: A multi-object assistance based network for brachial plexus segmentation in ultrasound images.Medical Image Analysis, 80:102511, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:58.108481Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:5d08b6bd99cd7ff29d3d776719759de544705687a1e2beccf95714a4402eba3f","observation_id":"8ba6ebf5-2be4-4c6a-877d-f14e9e18a50d","resolution":{"observed_at":"2026-08-03T11:49:58.108481Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.06799","last_updated":"2023-11-30T18:05:07Z","snapshot_observed_at":"2026-08-10T01:01:42.686054Z","submitted_at":"2022-07-14T10:23:17Z","title":"MMOTU: A Multi-Modality Ovarian Tumor Ultrasound Image Dataset for Unsupervised Cross-Domain Semantic Segmentation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.06799","snapshot_observed_at":"2026-08-03T11:49:58.185272Z","title":"Mmotu: A multi-modality ovarian tumor ultrasound image dataset for unsupervised cross-domain semantic segmentation.arXiv preprint arXiv:2207.06799, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:58.185272Z"},"links":{"cited_paper":"/paper/2207.06799","citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:91d5cce14fd3441f8ca3ed613f7681e535ec69cef83f39f7b3c198babeeb0889","observation_id":"0a8e8821-1757-45f9-9b57-d6e0712bec0f","resolution":{"observed_at":"2026-08-03T11:49:58.185272Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:58.271419Z","title":"Micro-ultrasound prostate segmentation dataset.URL: https://doi","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:58.271419Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:12531cbfacc3a5b3ec9d0057bb08b402e4c561495bb7381fcb470a1036accb0a","observation_id":"71d98a01-0f02-4678-8a0e-8b7a3e62d894","resolution":{"observed_at":"2026-08-03T11:49:58.271419Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:58.351954Z","title":"Thyroid region prior guided attention for ultrasound segmentation of thyroid nodules.Computers in biology and medicine, 155:106389, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:58.351954Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:b868a0ab8b969159bf65476d96a41347f389ebfaf898980641e3b6638a710b09","observation_id":"6d234554-8b33-4c77-b246-548e107666e7","resolution":{"observed_at":"2026-08-03T11:49:58.351954Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:58.455657Z","title":"Luminous database: lumbar multifidus muscle segmentation from ultrasound images.BMC Musculoskeletal Disorders, 21(1):703, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:58.455657Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:4f1bada600e63cbba2b8d44df94babf7adcda826c9418f9fbc739d721b002da0","observation_id":"dbbcc199-e507-4e0c-b72f-4c572ee2aaa9","resolution":{"observed_at":"2026-08-03T11:49:58.455657Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:58.519761Z","title":"FALLMUD: FAscicle Lower Leg Muscle Ultrasound Dataset","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:58.519761Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:a60dd7c481bb96b52fca3de97935ba2b30221a2d484028ea30053ad49646a049","observation_id":"1df065cf-3dc4-474b-8979-3859d555aeb2","resolution":{"observed_at":"2026-08-03T11:49:58.519761Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:58.593873Z","title":"Deep learning for segmentation using an open large-scale dataset in 2d echocardiography.IEEE transactions on medical imaging, 38(9):2198– 2210, 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:58.593873Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:ee443104708f9a89921d0d74cd771b10a4b3936c8a0e55a0c9ace2ba307b4807","observation_id":"88033a32-86c3-4888-8d84-bd429490a014","resolution":{"observed_at":"2026-08-03T11:49:58.593873Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:58.688512Z","title":"Unity Imaging Echocardiography Datasets","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:58.688512Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:c793b8130a9968909c754fee4872d931df284a18de12c8496eb584034f24d95d","observation_id":"58a18ada-14b7-40b4-b108-f6f41f6bd40a","resolution":{"observed_at":"2026-08-03T11:49:58.688512Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:58.695333Z","title":"Echocp: An echocardiography dataset in contrast transthoracic echocardiography for patent foramen ovale diagnosis","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:58.695333Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:7914a863242b157af474c69bdce4fce83e5c3fa6e6304aa2d99b85305c709feb","observation_id":"5ae98526-484d-440b-a442-b5cefa4b44b0","resolution":{"observed_at":"2026-08-03T11:49:58.695333Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:58.764085Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:58.764085Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:493a3d2c2b13bd6d0c489e7d97b218f1eb6ec4b3a239aa6b70c8ede1857b463f","observation_id":"63ab4908-c2be-4f11-9891-f5813621376e","resolution":{"observed_at":"2026-08-03T11:49:58.764085Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:58.926074Z","title":"Graphecho: Graph-driven unsuper- vised domain adaptation for echocardiogram video segmentation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:58.926074Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:a2a4755351882d06f5f7c711c5a86b6cdf99317b118dce07b2bd5ce96273a7f5","observation_id":"78bd8e37-4df2-4c19-b96e-652c80442a42","resolution":{"observed_at":"2026-08-03T11:49:58.926074Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:59.068505Z","title":"Mr to ultrasound registration for prostate challenge-dataset","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:59.068505Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:8c826e011df3eb973d4bb53695cbf891dd43c70d9426b86dab543e9e8bdd6f3f","observation_id":"41df533b-65e9-4134-9507-f07dbff6f4aa","resolution":{"observed_at":"2026-08-03T11:49:59.068505Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:59.169220Z","title":"Thyroid Ultrasound Cine-clip, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:59.169220Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:f5beb4c603b00acc61b4a0fcda035c4f1c37e22dbe9cb5121368a4917992048d","observation_id":"7393f650-a258-45fd-a347-ffc439cb54f7","resolution":{"observed_at":"2026-08-03T11:49:59.169220Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:59.312297Z","title":"Multi-task learning for thyroid nodule segmentation with thyroid region prior","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:59.312297Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:6cfbf54a0572acd532f408d231d1b5d1e4131ed6724f6f22629f1020c54aafb0","observation_id":"37b7316f-34b3-4171-93b1-3bd325d0b51f","resolution":{"observed_at":"2026-08-03T11:49:59.312297Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:59.433917Z","title":"Tracked 3d ultrasound and deep neural network-based thyroid segmentation reduce interobserver variability in thyroid volumetry.Plos one, 17(7):e0268550, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:59.433917Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:0c9ab7266131e4947c2cf8e43937d3ee0fcf1202a5f8b3d48b8d3ebc0e999514","observation_id":"302a239e-3e26-4996-b062-1b6e03c6ecff","resolution":{"observed_at":"2026-08-03T11:49:59.433917Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:59.524283Z","title":"An open access thyroid ultrasound image database","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:59.524283Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:163fc88f4716e3006493578645c4f593500dd1e3936fd83b21130419b5e69d95","observation_id":"4331ae5c-1e16-4cfd-8863-cb3eb8106d13","resolution":{"observed_at":"2026-08-03T11:49:59.524283Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:59.625569Z","title":"Fast and accurate u-net model for fetal ultrasound image segmentation.Ultrasonic imaging, 44(1):25–38, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:59.625569Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:d9ebcce5889fdb470c05a6465c4d06609390c38b5ff976aa39cf41fcf2a316c0","observation_id":"d51870b8-e9a0-4dd7-bd85-6148115c89eb","resolution":{"observed_at":"2026-08-03T11:49:59.625569Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:59.729401Z","title":"Acouslic-ai challenge report: Fetal abdominal circumference measurement on blind-sweep ultrasound data from low-income countries.Medical image analysis, 105:103640, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:59.729401Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:b2ef220bbc6254689cc99d29fc4addc2cb649756b382a99fce041e4b197c74b7","observation_id":"197e9dbc-ee67-4faf-af15-085c76b30195","resolution":{"observed_at":"2026-08-03T11:49:59.729401Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:59.804560Z","title":"Fetal abdominal structures segmentation dataset using ultrasonic images.Mendeley Data, 1:1, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:59.804560Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:3d99280cc853853cc17f8f6e8e20505fe446d9728a4e840b0f318800670a7ee1","observation_id":"bea19ad1-8fe3-46f9-bb13-de15d049a8ab","resolution":{"observed_at":"2026-08-03T11:49:59.804560Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:59.910759Z","title":"Focus: four-chamber ultrasound image dataset for fetal cardiac biometric measurement.Zenodo10, 5281, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:59.910759Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:35c19785baf97e49c20b44e3a07ba0a8815d3368093d1276620506c2c1c340fe","observation_id":"8d78e0c7-e280-4bf9-8264-73dfe554cd4f","resolution":{"observed_at":"2026-08-03T11:49:59.910759Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:49:59.984967Z","title":"Automated measurement of fetal head circumference using 2d ultrasound images.PloS one, 13(8):e0200412, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-03T11:49:59.984967Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:b3f342a73671a7ff937cb614365b3b0aea68dd303daa83ee4f39783286eb1e1a","observation_id":"a10f6ddf-97a1-4f3a-8e39-5467cc452562","resolution":{"observed_at":"2026-08-03T11:49:59.984967Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:50:00.160389Z","title":"Automated breast ultrasound lesions detection using convolutional neural networks.IEEE journal of biomedical and health informatics, 22(4):1218–1226, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-03T11:50:00.160389Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:6aaed568fc9db5160307ecd413de1ffcab58c7fb186626ee2d12d34634532ef8","observation_id":"6fa201b4-1c02-4e14-9550-0325ea28307e","resolution":{"observed_at":"2026-08-03T11:50:00.160389Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:50:00.297176Z","title":"Dataset of breast ultrasound images","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-03T11:50:00.297176Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:107ef34eda135e6bdcc9c9be0271239ad855900805efca918f7d047a4f51d2ce","observation_id":"f758a0c2-1aff-4845-b660-39964d8e16a1","resolution":{"observed_at":"2026-08-03T11:50:00.297176Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:50:00.425282Z","title":"Memory-efficient transformer network with feature fusion for breast tumor segmentation and classification task.Engineering Applications of Artificial Intelligence, 127:107292, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-03T11:50:00.425282Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:9409eeefc0949ed535da82895f5f31c695363fd95e6a7df6ae71b06dc7225fad","observation_id":"18ebaf8d-8658-40b6-ba3b-61f6dd1f838b","resolution":{"observed_at":"2026-08-03T11:50:00.425282Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:50:00.593124Z","title":"An open-access breast lesion ultrasound image database: Applicable in artificial intelligence studies.Computers in Biology and Medicine, 152:106438, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-03T11:50:00.593124Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:b37c8ef748767f4a7e617cad2c47d7d78739071dd0174b1493c1811a839ef374","observation_id":"b3e0f665-cee4-4e3d-b0b3-9f1c13f9418b","resolution":{"observed_at":"2026-08-03T11:50:00.593124Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:50:00.762893Z","title":"Segmentation and recognition of breast ultrasound images based on an expanded u-net.Plos one, 16(6):e0253202, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-03T11:50:00.762893Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:69de155de761da9f27aec9a1452c23bc6dee093ea78b8be2734c94644c871fd7","observation_id":"cdd0b415-38ec-40e0-a6c6-4accc6d3a3c4","resolution":{"observed_at":"2026-08-03T11:50:00.762893Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:50:00.934407Z","title":"The open kidney ultrasound data set","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-03T11:50:00.934407Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:86706ad36468376ed49413ee912a9b8004e45dda0d2890bd8b56170446d2f90c","observation_id":"e554e162-1c0a-4185-bdc9-327afdca639e","resolution":{"observed_at":"2026-08-03T11:50:00.934407Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:50:01.092121Z","title":"Curated benchmark dataset for ultrasound based breast lesion analysis.Scientific Data, 11(1):148, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-03T11:50:01.092121Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:f0249beda5b49f9daba294e4f6908b8b49909159024956f3b258434e9eaee567","observation_id":"d6ecc5e7-9a66-4272-9851-e3ab04b248b0","resolution":{"observed_at":"2026-08-03T11:50:01.092121Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:50:01.177360Z","title":"Common Carotid Artery Ultrasound Images, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-03T11:50:01.177360Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:f619f73336058981b632175fddfb69cd28c34209bca71f73bda697b24b83ea21","observation_id":"889ef938-70c4-4e9c-a3c1-b561a86844da","resolution":{"observed_at":"2026-08-03T11:50:01.177360Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:50:01.273853Z","title":"Algorithm guided outlining of 105 pancreatic cancer liver metastases in ultrasound.Scientific Reports, 7(1):12779, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-03T11:50:01.273853Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:8cbaaa4cb39ccf8858ffdbe228b43531291e2d4a174cbadaaaffc02d773d3634","observation_id":"8aebdb01-8d26-4ad9-b156-c4c415e83a2f","resolution":{"observed_at":"2026-08-03T11:50:01.273853Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T11:50:01.382249Z","title":"Please segment the suspicious tumor region in this breast ultrasound image","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-03T11:50:01.382249Z"},"links":{"citing_paper":"/paper/2607.29200"},"observation_digest":"sha256:f9c5390310cb3a66c6871daf34e6f69b5047627bbd0c497a1cec2b27e63e8477","observation_id":"bfbdabf1-3aa6-4df6-994b-1d522f0b4c71","resolution":{"observed_at":"2026-08-03T11:50:01.382249Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.29200","last_updated":"2026-07-31T09:19:49Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T21:46:42.253813Z","submitted_at":"2026-07-31T09:19:49Z","title":"UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation"},"reference_resolution":{"displayed":63,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":61,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":63},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 0 inbound Pith citation observations for arXiv:2607.29200."}