{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:RJIYCWKPIZMLEAM5ITLQH3HQDF","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"a316f0e461b677951063010ddd3433347b886d81df75518ba8866f713e2fcfd4","cross_cats_sorted":["cs.AI","cs.LG","eess.IV","eess.SP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-06T16:44:03Z","title_canon_sha256":"9a12895fa91a5e5dc653450b653bdd0057354b38ec480c3dbc6205a94206455c"},"schema_version":"1.0","source":{"id":"2304.03209","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.03209","created_at":"2026-07-05T06:31:31Z"},{"alias_kind":"arxiv_version","alias_value":"2304.03209v2","created_at":"2026-07-05T06:31:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.03209","created_at":"2026-07-05T06:31:31Z"},{"alias_kind":"pith_short_12","alias_value":"RJIYCWKPIZML","created_at":"2026-07-05T06:31:31Z"},{"alias_kind":"pith_short_16","alias_value":"RJIYCWKPIZMLEAM5","created_at":"2026-07-05T06:31:31Z"},{"alias_kind":"pith_short_8","alias_value":"RJIYCWKP","created_at":"2026-07-05T06:31:31Z"}],"graph_snapshots":[{"event_id":"sha256:6c761c1e7aa619e691000798ee636e5c901fe625b32a3af45a2dd6d2a21adce3","target":"graph","created_at":"2026-07-05T06:31:31Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2304.03209/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Integrating high-level semantically correlated contents and low-level anatomical features is of central importance in medical image segmentation. Towards this end, recent deep learning-based medical segmentation methods have shown great promise in better modeling such information. However, convolution operators for medical segmentation typically operate on regular grids, which inherently blur the high-frequency regions, i.e., boundary regions. In this work, we propose MORSE, a generic implicit neural rendering framework designed at an anatomical level to assist learning in medical image segmen","authors_text":"Chenyu You, James S. Duncan, Lawrence Staib, Weicheng Dai, Yifei Min","cross_cats":["cs.AI","cs.LG","eess.IV","eess.SP"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-06T16:44:03Z","title":"Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.03209","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:22279f3a6a082318e99f43d7893426a1018645b319dd139569a149f8b6a1f862","target":"record","created_at":"2026-07-05T06:31:31Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"a316f0e461b677951063010ddd3433347b886d81df75518ba8866f713e2fcfd4","cross_cats_sorted":["cs.AI","cs.LG","eess.IV","eess.SP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-04-06T16:44:03Z","title_canon_sha256":"9a12895fa91a5e5dc653450b653bdd0057354b38ec480c3dbc6205a94206455c"},"schema_version":"1.0","source":{"id":"2304.03209","kind":"arxiv","version":2}},"canonical_sha256":"8a5181594f4658b2019d44d703ecf0196db2889b46a657e52c96def34ad75e0e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8a5181594f4658b2019d44d703ecf0196db2889b46a657e52c96def34ad75e0e","first_computed_at":"2026-07-05T06:31:31.753389Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:31:31.753389Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Msl7Tz8OtDWk8ukHN2OmKv9Ah0AHyzERg9DSpHCM9KQCrkylza5ZtytZQEohHVhKeHvRrPiNUkfFNBq9jImHAw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:31:31.753876Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.03209","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:22279f3a6a082318e99f43d7893426a1018645b319dd139569a149f8b6a1f862","sha256:6c761c1e7aa619e691000798ee636e5c901fe625b32a3af45a2dd6d2a21adce3"],"state_sha256":"a1d0ce1a5885c652e3739cc395e08c68b2e9d87b893bbbd0607240403980ad8d"}