{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:6KB7EJMYYTR2QQN2AOJBZD7NWX","short_pith_number":"pith:6KB7EJMY","schema_version":"1.0","canonical_sha256":"f283f22598c4e3a841ba03921c8fedb5cbbc670ef6f675396fcf2bbc25ef46a9","source":{"kind":"arxiv","id":"1604.02677","version":1},"attestation_state":"computed","paper":{"title":"DCAN: Deep Contour-Aware Networks for Accurate Gland Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hao Chen, Lequan Yu, Pheng-Ann Heng, Xiaojuan Qi","submitted_at":"2016-04-10T12:12:24Z","abstract_excerpt":"The morphology of glands has been used routinely by pathologists to assess the malignancy degree of adenocarcinomas. Accurate segmentation of glands from histology images is a crucial step to obtain reliable morphological statistics for quantitative diagnosis. In this paper, we proposed an efficient deep contour-aware network (DCAN) to solve this challenging problem under a unified multi-task learning framework. In the proposed network, multi-level contextual features from the hierarchical architecture are explored with auxiliary supervision for accurate gland segmentation. When incorporated w"},"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":"1604.02677","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-04-10T12:12:24Z","cross_cats_sorted":[],"title_canon_sha256":"18904b9d12150434a83c992b55d19f5e08c66547673b756bac82a9a4c3cdca89","abstract_canon_sha256":"b7314f1dcdbbaf8d5d2f402d92d85958f55a7fc3219cbf7f8b4fc0fe6bbef786"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:17:22.441107Z","signature_b64":"u3ufa3CFWTaHAN9bbllwOik9NKGf15AKlZuB8rwsAhWtm9dJhCWSQGYWFjNV6OFjKqHqX2VQC+qKFupE5mCpDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f283f22598c4e3a841ba03921c8fedb5cbbc670ef6f675396fcf2bbc25ef46a9","last_reissued_at":"2026-05-18T01:17:22.440685Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:17:22.440685Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"DCAN: Deep Contour-Aware Networks for Accurate Gland Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hao Chen, Lequan Yu, Pheng-Ann Heng, Xiaojuan Qi","submitted_at":"2016-04-10T12:12:24Z","abstract_excerpt":"The morphology of glands has been used routinely by pathologists to assess the malignancy degree of adenocarcinomas. Accurate segmentation of glands from histology images is a crucial step to obtain reliable morphological statistics for quantitative diagnosis. In this paper, we proposed an efficient deep contour-aware network (DCAN) to solve this challenging problem under a unified multi-task learning framework. In the proposed network, multi-level contextual features from the hierarchical architecture are explored with auxiliary supervision for accurate gland segmentation. When incorporated w"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1604.02677","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":""},"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":"1604.02677","created_at":"2026-05-18T01:17:22.440752+00:00"},{"alias_kind":"arxiv_version","alias_value":"1604.02677v1","created_at":"2026-05-18T01:17:22.440752+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1604.02677","created_at":"2026-05-18T01:17:22.440752+00:00"},{"alias_kind":"pith_short_12","alias_value":"6KB7EJMYYTR2","created_at":"2026-05-18T12:30:01.593930+00:00"},{"alias_kind":"pith_short_16","alias_value":"6KB7EJMYYTR2QQN2","created_at":"2026-05-18T12:30:01.593930+00:00"},{"alias_kind":"pith_short_8","alias_value":"6KB7EJMY","created_at":"2026-05-18T12:30:01.593930+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/6KB7EJMYYTR2QQN2AOJBZD7NWX","json":"https://pith.science/pith/6KB7EJMYYTR2QQN2AOJBZD7NWX.json","graph_json":"https://pith.science/api/pith-number/6KB7EJMYYTR2QQN2AOJBZD7NWX/graph.json","events_json":"https://pith.science/api/pith-number/6KB7EJMYYTR2QQN2AOJBZD7NWX/events.json","paper":"https://pith.science/paper/6KB7EJMY"},"agent_actions":{"view_html":"https://pith.science/pith/6KB7EJMYYTR2QQN2AOJBZD7NWX","download_json":"https://pith.science/pith/6KB7EJMYYTR2QQN2AOJBZD7NWX.json","view_paper":"https://pith.science/paper/6KB7EJMY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1604.02677&json=true","fetch_graph":"https://pith.science/api/pith-number/6KB7EJMYYTR2QQN2AOJBZD7NWX/graph.json","fetch_events":"https://pith.science/api/pith-number/6KB7EJMYYTR2QQN2AOJBZD7NWX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6KB7EJMYYTR2QQN2AOJBZD7NWX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6KB7EJMYYTR2QQN2AOJBZD7NWX/action/storage_attestation","attest_author":"https://pith.science/pith/6KB7EJMYYTR2QQN2AOJBZD7NWX/action/author_attestation","sign_citation":"https://pith.science/pith/6KB7EJMYYTR2QQN2AOJBZD7NWX/action/citation_signature","submit_replication":"https://pith.science/pith/6KB7EJMYYTR2QQN2AOJBZD7NWX/action/replication_record"}},"created_at":"2026-05-18T01:17:22.440752+00:00","updated_at":"2026-05-18T01:17:22.440752+00:00"}