{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:WQ6FKSA6XZSQFJI42HHQ5ZEAYH","short_pith_number":"pith:WQ6FKSA6","canonical_record":{"source":{"id":"2501.09116","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-01-15T19:52:02Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"333c0de03066314d6f243f2b4e71aa438c2a3d724266dfc641b2c5dcdefba9e7","abstract_canon_sha256":"8fbf20027173d615353f589ba5eb381adddd158e1baf2186b4bca6a3708e5b52"},"schema_version":"1.0"},"canonical_sha256":"b43c55481ebe6502a51cd1cf0ee480c1d7c34be30b7e2c1a0645ace8c312e550","source":{"kind":"arxiv","id":"2501.09116","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.09116","created_at":"2026-07-05T10:01:41Z"},{"alias_kind":"arxiv_version","alias_value":"2501.09116v1","created_at":"2026-07-05T10:01:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.09116","created_at":"2026-07-05T10:01:41Z"},{"alias_kind":"pith_short_12","alias_value":"WQ6FKSA6XZSQ","created_at":"2026-07-05T10:01:41Z"},{"alias_kind":"pith_short_16","alias_value":"WQ6FKSA6XZSQFJI4","created_at":"2026-07-05T10:01:41Z"},{"alias_kind":"pith_short_8","alias_value":"WQ6FKSA6","created_at":"2026-07-05T10:01:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:WQ6FKSA6XZSQFJI42HHQ5ZEAYH","target":"record","payload":{"canonical_record":{"source":{"id":"2501.09116","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-01-15T19:52:02Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"333c0de03066314d6f243f2b4e71aa438c2a3d724266dfc641b2c5dcdefba9e7","abstract_canon_sha256":"8fbf20027173d615353f589ba5eb381adddd158e1baf2186b4bca6a3708e5b52"},"schema_version":"1.0"},"canonical_sha256":"b43c55481ebe6502a51cd1cf0ee480c1d7c34be30b7e2c1a0645ace8c312e550","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:01:41.962991Z","signature_b64":"Wb2YvY/mBYT36xIMd1/lexczqxrfzk/3zHTxKG1AznDMKCiL6+tim9UGHY5jzZcxJcx5C/Fhhq+bdYOR8MWeAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b43c55481ebe6502a51cd1cf0ee480c1d7c34be30b7e2c1a0645ace8c312e550","last_reissued_at":"2026-07-05T10:01:41.962540Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:01:41.962540Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.09116","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:01:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+7bioiKKUaImxKH7tuRYZmbiv95xuOpmy8ctdT1DdYy0WXBC0Mb++lQQzjAlPaZhUI/5AYI75GSuh8Cpq4dBDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T18:16:30.253257Z"},"content_sha256":"9675367661d7996f96f9aee97b6bfcc5d4cd6dfe685c7795124355e73b0cd011","schema_version":"1.0","event_id":"sha256:9675367661d7996f96f9aee97b6bfcc5d4cd6dfe685c7795124355e73b0cd011"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:WQ6FKSA6XZSQFJI42HHQ5ZEAYH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Distance Map Regression Network with Shape-aware Loss for Imbalanced Medical Image Segmentation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Donghai Liao, Huiyu Li, Said Boumaraf, Xiabi Liu, Xiaohong Ma, Xiaopeng Gong","submitted_at":"2025-01-15T19:52:02Z","abstract_excerpt":"Small object segmentation, like tumor segmentation, is a difficult and critical task in the field of medical image analysis. Although deep learning based methods have achieved promising performance, they are restricted to the use of binary segmentation mask. Inspired by the rigorous mapping between binary segmentation mask and distance map, we adopt distance map as a novel ground truth and employ a network to fulfill the computation of distance map. Specially, we propose a new segmentation framework that incorporates the existing binary segmentation network and a light weight regression networ"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.09116","kind":"arxiv","version":1},"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/2501.09116/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":"2026-07-05T10:01:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VpG7obGRPP+NLBGSuTLnW753RXohWKD+8ohYWUVbqkWZ0ROiH4vYQZZ40wdbqb1aIWpF9yKV2Ame9z0pHZ9YBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T18:16:30.254126Z"},"content_sha256":"10446148f4f1a8884fbf1a48a29df468acaa81572abb778c1f50668e645d6b1b","schema_version":"1.0","event_id":"sha256:10446148f4f1a8884fbf1a48a29df468acaa81572abb778c1f50668e645d6b1b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WQ6FKSA6XZSQFJI42HHQ5ZEAYH/bundle.json","state_url":"https://pith.science/pith/WQ6FKSA6XZSQFJI42HHQ5ZEAYH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WQ6FKSA6XZSQFJI42HHQ5ZEAYH/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":"2026-08-20T18:16:30Z","links":{"resolver":"https://pith.science/pith/WQ6FKSA6XZSQFJI42HHQ5ZEAYH","bundle":"https://pith.science/pith/WQ6FKSA6XZSQFJI42HHQ5ZEAYH/bundle.json","state":"https://pith.science/pith/WQ6FKSA6XZSQFJI42HHQ5ZEAYH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WQ6FKSA6XZSQFJI42HHQ5ZEAYH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:WQ6FKSA6XZSQFJI42HHQ5ZEAYH","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":"8fbf20027173d615353f589ba5eb381adddd158e1baf2186b4bca6a3708e5b52","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-01-15T19:52:02Z","title_canon_sha256":"333c0de03066314d6f243f2b4e71aa438c2a3d724266dfc641b2c5dcdefba9e7"},"schema_version":"1.0","source":{"id":"2501.09116","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.09116","created_at":"2026-07-05T10:01:41Z"},{"alias_kind":"arxiv_version","alias_value":"2501.09116v1","created_at":"2026-07-05T10:01:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.09116","created_at":"2026-07-05T10:01:41Z"},{"alias_kind":"pith_short_12","alias_value":"WQ6FKSA6XZSQ","created_at":"2026-07-05T10:01:41Z"},{"alias_kind":"pith_short_16","alias_value":"WQ6FKSA6XZSQFJI4","created_at":"2026-07-05T10:01:41Z"},{"alias_kind":"pith_short_8","alias_value":"WQ6FKSA6","created_at":"2026-07-05T10:01:41Z"}],"graph_snapshots":[{"event_id":"sha256:10446148f4f1a8884fbf1a48a29df468acaa81572abb778c1f50668e645d6b1b","target":"graph","created_at":"2026-07-05T10:01:41Z","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/2501.09116/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Small object segmentation, like tumor segmentation, is a difficult and critical task in the field of medical image analysis. Although deep learning based methods have achieved promising performance, they are restricted to the use of binary segmentation mask. Inspired by the rigorous mapping between binary segmentation mask and distance map, we adopt distance map as a novel ground truth and employ a network to fulfill the computation of distance map. Specially, we propose a new segmentation framework that incorporates the existing binary segmentation network and a light weight regression networ","authors_text":"Donghai Liao, Huiyu Li, Said Boumaraf, Xiabi Liu, Xiaohong Ma, Xiaopeng Gong","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-01-15T19:52:02Z","title":"Deep Distance Map Regression Network with Shape-aware Loss for Imbalanced Medical Image Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.09116","kind":"arxiv","version":1},"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":"sha256:9675367661d7996f96f9aee97b6bfcc5d4cd6dfe685c7795124355e73b0cd011","target":"record","created_at":"2026-07-05T10:01:41Z","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":"8fbf20027173d615353f589ba5eb381adddd158e1baf2186b4bca6a3708e5b52","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2025-01-15T19:52:02Z","title_canon_sha256":"333c0de03066314d6f243f2b4e71aa438c2a3d724266dfc641b2c5dcdefba9e7"},"schema_version":"1.0","source":{"id":"2501.09116","kind":"arxiv","version":1}},"canonical_sha256":"b43c55481ebe6502a51cd1cf0ee480c1d7c34be30b7e2c1a0645ace8c312e550","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b43c55481ebe6502a51cd1cf0ee480c1d7c34be30b7e2c1a0645ace8c312e550","first_computed_at":"2026-07-05T10:01:41.962540Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:01:41.962540Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Wb2YvY/mBYT36xIMd1/lexczqxrfzk/3zHTxKG1AznDMKCiL6+tim9UGHY5jzZcxJcx5C/Fhhq+bdYOR8MWeAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:01:41.962991Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.09116","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9675367661d7996f96f9aee97b6bfcc5d4cd6dfe685c7795124355e73b0cd011","sha256:10446148f4f1a8884fbf1a48a29df468acaa81572abb778c1f50668e645d6b1b"],"state_sha256":"d41b4aeb25cefc6ab237d805fde68df1e63f9df91cff059c41a30fe217938a76"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ai+jYS8MADhA6pIPbIfAsMDzGejWhZom/QEIalRnNpYWX1ANBKP/HD9CpirJ6fbethLyGjq8De6A8BkTqJraCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T18:16:30.261369Z","bundle_sha256":"37d612f74ec00e4ddcee4f72048e3498a53afb35cba4d02aeac021efc8d68293"}}