{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:H7YNKCY4LOWY5VOXSDOMYPNA7V","short_pith_number":"pith:H7YNKCY4","canonical_record":{"source":{"id":"1908.10454","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-08-27T20:25:52Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"3b8e67c4f3d35caad9219334f8ed6d9e56511e3b6f042522678b98a4fbb8f7fa","abstract_canon_sha256":"b3e7cb616d3cfc3974727cc620577c12a2df8b153b101946415d1cadc8ebecff"},"schema_version":"1.0"},"canonical_sha256":"3ff0d50b1c5bad8ed5d790dccc3da0fd7bc7f9a4c90afbc4103de04b4593c694","source":{"kind":"arxiv","id":"1908.10454","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.10454","created_at":"2026-07-05T00:40:14Z"},{"alias_kind":"arxiv_version","alias_value":"1908.10454v2","created_at":"2026-07-05T00:40:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.10454","created_at":"2026-07-05T00:40:14Z"},{"alias_kind":"pith_short_12","alias_value":"H7YNKCY4LOWY","created_at":"2026-07-05T00:40:14Z"},{"alias_kind":"pith_short_16","alias_value":"H7YNKCY4LOWY5VOX","created_at":"2026-07-05T00:40:14Z"},{"alias_kind":"pith_short_8","alias_value":"H7YNKCY4","created_at":"2026-07-05T00:40:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:H7YNKCY4LOWY5VOXSDOMYPNA7V","target":"record","payload":{"canonical_record":{"source":{"id":"1908.10454","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-08-27T20:25:52Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"3b8e67c4f3d35caad9219334f8ed6d9e56511e3b6f042522678b98a4fbb8f7fa","abstract_canon_sha256":"b3e7cb616d3cfc3974727cc620577c12a2df8b153b101946415d1cadc8ebecff"},"schema_version":"1.0"},"canonical_sha256":"3ff0d50b1c5bad8ed5d790dccc3da0fd7bc7f9a4c90afbc4103de04b4593c694","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:40:14.227713Z","signature_b64":"n5Z+m9cW9XaXTDOlg6zyqwo0fp23siVuw1v+4BeYLc36TuoAkXLSJEhBQKpUB/bZdBjxDJty//CpnvkzkCveDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3ff0d50b1c5bad8ed5d790dccc3da0fd7bc7f9a4c90afbc4103de04b4593c694","last_reissued_at":"2026-07-05T00:40:14.227301Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:40:14.227301Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1908.10454","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:40:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eUaKT3DraqYrYSGo0SMm2rcX++qetzyKyekkrbI3Hs1TtnVusjYbGvBKIGNrWjdrELobkNEUo8E3/AbClRT5DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T13:39:29.665120Z"},"content_sha256":"9a820218e35320b0df4dd966a25ba689816951c945d18486eddc82fb108a5f94","schema_version":"1.0","event_id":"sha256:9a820218e35320b0df4dd966a25ba689816951c945d18486eddc82fb108a5f94"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:H7YNKCY4LOWY5VOXSDOMYPNA7V","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"eess.IV","authors_text":"Jeffrey Chiang, Laura Jeyaseelan, Nima Tajbakhsh, Qian Li, Xiaowei Ding, Zhihao Wu","submitted_at":"2019-08-27T20:25:52Z","abstract_excerpt":"The medical imaging literature has witnessed remarkable progress in high-performing segmentation models based on convolutional neural networks. Despite the new performance highs, the recent advanced segmentation models still require large, representative, and high quality annotated datasets. However, rarely do we have a perfect training dataset, particularly in the field of medical imaging, where data and annotations are both expensive to acquire. Recently, a large body of research has studied the problem of medical image segmentation with imperfect datasets, tackling two major dataset limitat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.10454","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1908.10454/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:40:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"epDLyL8Bjm7oHvW3WIRzaIzgPn52tRdTv5DigUASu525cwpYhMtUFKo3uHPzHF/aDYoxat/J9wHKJFMXJMAlDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T13:39:29.665524Z"},"content_sha256":"2b4f4329ffa11061715e50b75f094d771f12f6eede83e367341b3b03871ca50f","schema_version":"1.0","event_id":"sha256:2b4f4329ffa11061715e50b75f094d771f12f6eede83e367341b3b03871ca50f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/H7YNKCY4LOWY5VOXSDOMYPNA7V/bundle.json","state_url":"https://pith.science/pith/H7YNKCY4LOWY5VOXSDOMYPNA7V/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/H7YNKCY4LOWY5VOXSDOMYPNA7V/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-07T13:39:29Z","links":{"resolver":"https://pith.science/pith/H7YNKCY4LOWY5VOXSDOMYPNA7V","bundle":"https://pith.science/pith/H7YNKCY4LOWY5VOXSDOMYPNA7V/bundle.json","state":"https://pith.science/pith/H7YNKCY4LOWY5VOXSDOMYPNA7V/state.json","well_known_bundle":"https://pith.science/.well-known/pith/H7YNKCY4LOWY5VOXSDOMYPNA7V/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:H7YNKCY4LOWY5VOXSDOMYPNA7V","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":"b3e7cb616d3cfc3974727cc620577c12a2df8b153b101946415d1cadc8ebecff","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-08-27T20:25:52Z","title_canon_sha256":"3b8e67c4f3d35caad9219334f8ed6d9e56511e3b6f042522678b98a4fbb8f7fa"},"schema_version":"1.0","source":{"id":"1908.10454","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.10454","created_at":"2026-07-05T00:40:14Z"},{"alias_kind":"arxiv_version","alias_value":"1908.10454v2","created_at":"2026-07-05T00:40:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.10454","created_at":"2026-07-05T00:40:14Z"},{"alias_kind":"pith_short_12","alias_value":"H7YNKCY4LOWY","created_at":"2026-07-05T00:40:14Z"},{"alias_kind":"pith_short_16","alias_value":"H7YNKCY4LOWY5VOX","created_at":"2026-07-05T00:40:14Z"},{"alias_kind":"pith_short_8","alias_value":"H7YNKCY4","created_at":"2026-07-05T00:40:14Z"}],"graph_snapshots":[{"event_id":"sha256:2b4f4329ffa11061715e50b75f094d771f12f6eede83e367341b3b03871ca50f","target":"graph","created_at":"2026-07-05T00:40:14Z","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/1908.10454/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The medical imaging literature has witnessed remarkable progress in high-performing segmentation models based on convolutional neural networks. Despite the new performance highs, the recent advanced segmentation models still require large, representative, and high quality annotated datasets. However, rarely do we have a perfect training dataset, particularly in the field of medical imaging, where data and annotations are both expensive to acquire. Recently, a large body of research has studied the problem of medical image segmentation with imperfect datasets, tackling two major dataset limitat","authors_text":"Jeffrey Chiang, Laura Jeyaseelan, Nima Tajbakhsh, Qian Li, Xiaowei Ding, Zhihao Wu","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-08-27T20:25:52Z","title":"Embracing Imperfect Datasets: A Review of Deep Learning Solutions for Medical Image Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.10454","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":"sha256:9a820218e35320b0df4dd966a25ba689816951c945d18486eddc82fb108a5f94","target":"record","created_at":"2026-07-05T00:40:14Z","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":"b3e7cb616d3cfc3974727cc620577c12a2df8b153b101946415d1cadc8ebecff","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-08-27T20:25:52Z","title_canon_sha256":"3b8e67c4f3d35caad9219334f8ed6d9e56511e3b6f042522678b98a4fbb8f7fa"},"schema_version":"1.0","source":{"id":"1908.10454","kind":"arxiv","version":2}},"canonical_sha256":"3ff0d50b1c5bad8ed5d790dccc3da0fd7bc7f9a4c90afbc4103de04b4593c694","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3ff0d50b1c5bad8ed5d790dccc3da0fd7bc7f9a4c90afbc4103de04b4593c694","first_computed_at":"2026-07-05T00:40:14.227301Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:40:14.227301Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"n5Z+m9cW9XaXTDOlg6zyqwo0fp23siVuw1v+4BeYLc36TuoAkXLSJEhBQKpUB/bZdBjxDJty//CpnvkzkCveDw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:40:14.227713Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.10454","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9a820218e35320b0df4dd966a25ba689816951c945d18486eddc82fb108a5f94","sha256:2b4f4329ffa11061715e50b75f094d771f12f6eede83e367341b3b03871ca50f"],"state_sha256":"dfc1274bb049552eedc4a293a0bc8c66e1cb72eb531907bf103eaa906d6364a4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kJJiqKABGfe5yKUpEwEiUznN1QPQ5nGPahwQO2rNy0NbXFvwOOKdkH21ln7LBIa2sdLMqeDD5A4RjrH5cF0zAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T13:39:29.667508Z","bundle_sha256":"aa5111fd278a7f3efd5508ded402209804e4caac0ca25af35e5fe4a04b857df6"}}