{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:ODDQ3AUMXYEJYYVAN5JAN3AHYO","short_pith_number":"pith:ODDQ3AUM","schema_version":"1.0","canonical_sha256":"70c70d828cbe089c62a06f5206ec07c3a9a2a403d6ea7223570c0ebef59f45b9","source":{"kind":"arxiv","id":"2310.14197","version":2},"attestation_state":"computed","paper":{"title":"Diffusion-based Data Augmentation for Nuclei Image Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Guanbin Li, Haofeng Li, Siqi Liu, Wei Lou, Xiang Wan, Xinyi Yu, Yan Chen","submitted_at":"2023-10-22T06:16:16Z","abstract_excerpt":"Nuclei segmentation is a fundamental but challenging task in the quantitative analysis of histopathology images. Although fully-supervised deep learning-based methods have made significant progress, a large number of labeled images are required to achieve great segmentation performance. Considering that manually labeling all nuclei instances for a dataset is inefficient, obtaining a large-scale human-annotated dataset is time-consuming and labor-intensive. Therefore, augmenting a dataset with only a few labeled images to improve the segmentation performance is of significant research and appli"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2310.14197","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2023-10-22T06:16:16Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"115041d80fc149737ddff19f7111fb4f6cce9749907e3cdb4c74eb496b4e9583","abstract_canon_sha256":"42056d2ea1446a8d4d835a6a778ba53e0a28f32599739dc3008e0792f60c8512"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:35:22.145824Z","signature_b64":"jwisQBRc5JxodhKJiC5IA9xZMoWNNIBqCtCHJoN852N1030wO+bBx8oaL5cibLr8lI5hFPb01ZRN9Uj0hkyIAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"70c70d828cbe089c62a06f5206ec07c3a9a2a403d6ea7223570c0ebef59f45b9","last_reissued_at":"2026-07-05T07:35:22.145358Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:35:22.145358Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Diffusion-based Data Augmentation for Nuclei Image Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Guanbin Li, Haofeng Li, Siqi Liu, Wei Lou, Xiang Wan, Xinyi Yu, Yan Chen","submitted_at":"2023-10-22T06:16:16Z","abstract_excerpt":"Nuclei segmentation is a fundamental but challenging task in the quantitative analysis of histopathology images. Although fully-supervised deep learning-based methods have made significant progress, a large number of labeled images are required to achieve great segmentation performance. Considering that manually labeling all nuclei instances for a dataset is inefficient, obtaining a large-scale human-annotated dataset is time-consuming and labor-intensive. Therefore, augmenting a dataset with only a few labeled images to improve the segmentation performance is of significant research and appli"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.14197","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/2310.14197/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2310.14197","created_at":"2026-07-05T07:35:22.145413+00:00"},{"alias_kind":"arxiv_version","alias_value":"2310.14197v2","created_at":"2026-07-05T07:35:22.145413+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.14197","created_at":"2026-07-05T07:35:22.145413+00:00"},{"alias_kind":"pith_short_12","alias_value":"ODDQ3AUMXYEJ","created_at":"2026-07-05T07:35:22.145413+00:00"},{"alias_kind":"pith_short_16","alias_value":"ODDQ3AUMXYEJYYVA","created_at":"2026-07-05T07:35:22.145413+00:00"},{"alias_kind":"pith_short_8","alias_value":"ODDQ3AUM","created_at":"2026-07-05T07:35:22.145413+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ODDQ3AUMXYEJYYVAN5JAN3AHYO","json":"https://pith.science/pith/ODDQ3AUMXYEJYYVAN5JAN3AHYO.json","graph_json":"https://pith.science/api/pith-number/ODDQ3AUMXYEJYYVAN5JAN3AHYO/graph.json","events_json":"https://pith.science/api/pith-number/ODDQ3AUMXYEJYYVAN5JAN3AHYO/events.json","paper":"https://pith.science/paper/ODDQ3AUM"},"agent_actions":{"view_html":"https://pith.science/pith/ODDQ3AUMXYEJYYVAN5JAN3AHYO","download_json":"https://pith.science/pith/ODDQ3AUMXYEJYYVAN5JAN3AHYO.json","view_paper":"https://pith.science/paper/ODDQ3AUM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2310.14197&json=true","fetch_graph":"https://pith.science/api/pith-number/ODDQ3AUMXYEJYYVAN5JAN3AHYO/graph.json","fetch_events":"https://pith.science/api/pith-number/ODDQ3AUMXYEJYYVAN5JAN3AHYO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ODDQ3AUMXYEJYYVAN5JAN3AHYO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ODDQ3AUMXYEJYYVAN5JAN3AHYO/action/storage_attestation","attest_author":"https://pith.science/pith/ODDQ3AUMXYEJYYVAN5JAN3AHYO/action/author_attestation","sign_citation":"https://pith.science/pith/ODDQ3AUMXYEJYYVAN5JAN3AHYO/action/citation_signature","submit_replication":"https://pith.science/pith/ODDQ3AUMXYEJYYVAN5JAN3AHYO/action/replication_record"}},"created_at":"2026-07-05T07:35:22.145413+00:00","updated_at":"2026-07-05T07:35:22.145413+00:00"}