{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:QQBMIRWVZAMUBVPCON3PIYYPAY","short_pith_number":"pith:QQBMIRWV","schema_version":"1.0","canonical_sha256":"8402c446d5c81940d5e27376f4630f06044ed5d9d896794bfff78ed056b53405","source":{"kind":"arxiv","id":"1909.03253","version":1},"attestation_state":"computed","paper":{"title":"NuClick: From Clicks in the Nuclei to Nuclear Boundaries","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","eess.IV","stat.ML"],"primary_cat":"q-bio.QM","authors_text":"Mostafa Jahanifar, Nasir Rajpoot, Navid Alemi Koohbanani","submitted_at":"2019-09-07T11:52:19Z","abstract_excerpt":"Best performing nuclear segmentation methods are based on deep learning algorithms that require a large amount of annotated data. However, collecting annotations for nuclear segmentation is a very labor-intensive and time-consuming task. Thereby, providing a tool that can facilitate and speed up this procedure is very demanding. Here we propose a simple yet efficient framework based on convolutional neural networks, named NuClick, which can precisely segment nuclei boundaries by accepting a single point position (or click) inside each nucleus. Based on the clicked positions, inclusion and excl"},"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":"1909.03253","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2019-09-07T11:52:19Z","cross_cats_sorted":["cs.LG","eess.IV","stat.ML"],"title_canon_sha256":"4038d9478f1ee56891d8ac725ceab5a1dddd1fa85b482ee5471ad6c020b55688","abstract_canon_sha256":"03772331cc0538bd71933b5d7a06883e1ddca73bf00bde050a4cc8f217640b74"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:03:03.954594Z","signature_b64":"+yEZqBrKG9OS6l0NMV4/bbLqZnbpesWfGfStvVaIzxCVtSNsHN52h08HUpXTMX/I73tPytVCMNaIfj6wsPLZCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8402c446d5c81940d5e27376f4630f06044ed5d9d896794bfff78ed056b53405","last_reissued_at":"2026-07-05T00:03:03.954247Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:03:03.954247Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"NuClick: From Clicks in the Nuclei to Nuclear Boundaries","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","eess.IV","stat.ML"],"primary_cat":"q-bio.QM","authors_text":"Mostafa Jahanifar, Nasir Rajpoot, Navid Alemi Koohbanani","submitted_at":"2019-09-07T11:52:19Z","abstract_excerpt":"Best performing nuclear segmentation methods are based on deep learning algorithms that require a large amount of annotated data. However, collecting annotations for nuclear segmentation is a very labor-intensive and time-consuming task. Thereby, providing a tool that can facilitate and speed up this procedure is very demanding. Here we propose a simple yet efficient framework based on convolutional neural networks, named NuClick, which can precisely segment nuclei boundaries by accepting a single point position (or click) inside each nucleus. Based on the clicked positions, inclusion and excl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1909.03253","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/1909.03253/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":"1909.03253","created_at":"2026-07-05T00:03:03.954303+00:00"},{"alias_kind":"arxiv_version","alias_value":"1909.03253v1","created_at":"2026-07-05T00:03:03.954303+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1909.03253","created_at":"2026-07-05T00:03:03.954303+00:00"},{"alias_kind":"pith_short_12","alias_value":"QQBMIRWVZAMU","created_at":"2026-07-05T00:03:03.954303+00:00"},{"alias_kind":"pith_short_16","alias_value":"QQBMIRWVZAMUBVPC","created_at":"2026-07-05T00:03:03.954303+00:00"},{"alias_kind":"pith_short_8","alias_value":"QQBMIRWV","created_at":"2026-07-05T00:03:03.954303+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/QQBMIRWVZAMUBVPCON3PIYYPAY","json":"https://pith.science/pith/QQBMIRWVZAMUBVPCON3PIYYPAY.json","graph_json":"https://pith.science/api/pith-number/QQBMIRWVZAMUBVPCON3PIYYPAY/graph.json","events_json":"https://pith.science/api/pith-number/QQBMIRWVZAMUBVPCON3PIYYPAY/events.json","paper":"https://pith.science/paper/QQBMIRWV"},"agent_actions":{"view_html":"https://pith.science/pith/QQBMIRWVZAMUBVPCON3PIYYPAY","download_json":"https://pith.science/pith/QQBMIRWVZAMUBVPCON3PIYYPAY.json","view_paper":"https://pith.science/paper/QQBMIRWV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1909.03253&json=true","fetch_graph":"https://pith.science/api/pith-number/QQBMIRWVZAMUBVPCON3PIYYPAY/graph.json","fetch_events":"https://pith.science/api/pith-number/QQBMIRWVZAMUBVPCON3PIYYPAY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QQBMIRWVZAMUBVPCON3PIYYPAY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QQBMIRWVZAMUBVPCON3PIYYPAY/action/storage_attestation","attest_author":"https://pith.science/pith/QQBMIRWVZAMUBVPCON3PIYYPAY/action/author_attestation","sign_citation":"https://pith.science/pith/QQBMIRWVZAMUBVPCON3PIYYPAY/action/citation_signature","submit_replication":"https://pith.science/pith/QQBMIRWVZAMUBVPCON3PIYYPAY/action/replication_record"}},"created_at":"2026-07-05T00:03:03.954303+00:00","updated_at":"2026-07-05T00:03:03.954303+00:00"}