{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:N6J3G26ZYQ33XBUR553FQZ22RF","short_pith_number":"pith:N6J3G26Z","schema_version":"1.0","canonical_sha256":"6f93b36bd9c437bb8691ef7658675a894fb447d65e786ef1376556eecd6fd467","source":{"kind":"arxiv","id":"1807.05482","version":1},"attestation_state":"computed","paper":{"title":"Near Real-time Hippocampus Segmentation Using Patch-based Canonical Neural Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Duncan Gillies, Zhongliu Xie","submitted_at":"2018-07-15T03:23:28Z","abstract_excerpt":"Over the past decades, state-of-the-art medical image segmentation has heavily rested on signal processing paradigms, most notably registration-based label propagation and pair-wise patch comparison, which are generally slow despite a high segmentation accuracy. In recent years, deep learning has revolutionalized computer vision with many practices outperforming prior art, in particular the convolutional neural network (CNN) studies on image classification. Deep CNN has also started being applied to medical image segmentation lately, but generally involves long training and demanding memory re"},"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":"1807.05482","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-07-15T03:23:28Z","cross_cats_sorted":[],"title_canon_sha256":"be7462b376e5c0d5312344ee77367aaa47c3330c2b0dcbb1771051610b6040f5","abstract_canon_sha256":"7c7294beb3fda600344715f1603197559f160e89d3df3b50850217e7d6ad0b84"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:10:43.441819Z","signature_b64":"zYq5p6DODkE5qYK6yTwj34/NLTKrUpTCUExORJboG3SGKNn3zkIzv7TydX6YTUAAjicSDyLD3oySsbyYAdlLCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6f93b36bd9c437bb8691ef7658675a894fb447d65e786ef1376556eecd6fd467","last_reissued_at":"2026-05-18T00:10:43.441215Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:10:43.441215Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Near Real-time Hippocampus Segmentation Using Patch-based Canonical Neural Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Duncan Gillies, Zhongliu Xie","submitted_at":"2018-07-15T03:23:28Z","abstract_excerpt":"Over the past decades, state-of-the-art medical image segmentation has heavily rested on signal processing paradigms, most notably registration-based label propagation and pair-wise patch comparison, which are generally slow despite a high segmentation accuracy. In recent years, deep learning has revolutionalized computer vision with many practices outperforming prior art, in particular the convolutional neural network (CNN) studies on image classification. Deep CNN has also started being applied to medical image segmentation lately, but generally involves long training and demanding memory re"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.05482","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":"1807.05482","created_at":"2026-05-18T00:10:43.441308+00:00"},{"alias_kind":"arxiv_version","alias_value":"1807.05482v1","created_at":"2026-05-18T00:10:43.441308+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.05482","created_at":"2026-05-18T00:10:43.441308+00:00"},{"alias_kind":"pith_short_12","alias_value":"N6J3G26ZYQ33","created_at":"2026-05-18T12:32:40.477152+00:00"},{"alias_kind":"pith_short_16","alias_value":"N6J3G26ZYQ33XBUR","created_at":"2026-05-18T12:32:40.477152+00:00"},{"alias_kind":"pith_short_8","alias_value":"N6J3G26Z","created_at":"2026-05-18T12:32:40.477152+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/N6J3G26ZYQ33XBUR553FQZ22RF","json":"https://pith.science/pith/N6J3G26ZYQ33XBUR553FQZ22RF.json","graph_json":"https://pith.science/api/pith-number/N6J3G26ZYQ33XBUR553FQZ22RF/graph.json","events_json":"https://pith.science/api/pith-number/N6J3G26ZYQ33XBUR553FQZ22RF/events.json","paper":"https://pith.science/paper/N6J3G26Z"},"agent_actions":{"view_html":"https://pith.science/pith/N6J3G26ZYQ33XBUR553FQZ22RF","download_json":"https://pith.science/pith/N6J3G26ZYQ33XBUR553FQZ22RF.json","view_paper":"https://pith.science/paper/N6J3G26Z","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1807.05482&json=true","fetch_graph":"https://pith.science/api/pith-number/N6J3G26ZYQ33XBUR553FQZ22RF/graph.json","fetch_events":"https://pith.science/api/pith-number/N6J3G26ZYQ33XBUR553FQZ22RF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/N6J3G26ZYQ33XBUR553FQZ22RF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/N6J3G26ZYQ33XBUR553FQZ22RF/action/storage_attestation","attest_author":"https://pith.science/pith/N6J3G26ZYQ33XBUR553FQZ22RF/action/author_attestation","sign_citation":"https://pith.science/pith/N6J3G26ZYQ33XBUR553FQZ22RF/action/citation_signature","submit_replication":"https://pith.science/pith/N6J3G26ZYQ33XBUR553FQZ22RF/action/replication_record"}},"created_at":"2026-05-18T00:10:43.441308+00:00","updated_at":"2026-05-18T00:10:43.441308+00:00"}