{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:DHXHXE6JCPUUBGOZQQ2CEO52EI","short_pith_number":"pith:DHXHXE6J","schema_version":"1.0","canonical_sha256":"19ee7b93c913e94099d98434223bba223cf8bbb6618b0057576abc7c23943a25","source":{"kind":"arxiv","id":"1807.03434","version":1},"attestation_state":"computed","paper":{"title":"Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Eric P. Xing, Michael Kampffmeyer, Nanqing Dong, Wei Dai, Xiaodan Liang, Zeya Wang","submitted_at":"2018-07-10T01:18:40Z","abstract_excerpt":"The cardiothoracic ratio (CTR), a clinical metric of heart size in chest X-rays (CXRs), is a key indicator of cardiomegaly. Manual measurement of CTR is time-consuming and can be affected by human subjectivity, making it desirable to design computer-aided systems that assist clinicians in the diagnosis process. Automatic CTR estimation through chest organ segmentation, however, requires large amounts of pixel-level annotated data, which is often unavailable. To alleviate this problem, we propose an unsupervised domain adaptation framework based on adversarial networks. The framework learns dom"},"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":"1807.03434","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-07-10T01:18:40Z","cross_cats_sorted":[],"title_canon_sha256":"525e875ec2efff221ea2eb399d86a153b1652d231c27d7d97b4bc4ab6456aae2","abstract_canon_sha256":"3ee248f5439703bcffb734da1c8f6a5a6b95e31cb7170e32af71a80c70da6a1d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:11:10.441339Z","signature_b64":"V2fEagSARH9/3LWLIuONsVbGgV1JPc71HgkurYhXkuAn+mZkL2eKhEwDe3UXgPClgcQ6Kfwr5mOHlM9uohxDBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"19ee7b93c913e94099d98434223bba223cf8bbb6618b0057576abc7c23943a25","last_reissued_at":"2026-05-18T00:11:10.440630Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:11:10.440630Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Eric P. Xing, Michael Kampffmeyer, Nanqing Dong, Wei Dai, Xiaodan Liang, Zeya Wang","submitted_at":"2018-07-10T01:18:40Z","abstract_excerpt":"The cardiothoracic ratio (CTR), a clinical metric of heart size in chest X-rays (CXRs), is a key indicator of cardiomegaly. Manual measurement of CTR is time-consuming and can be affected by human subjectivity, making it desirable to design computer-aided systems that assist clinicians in the diagnosis process. Automatic CTR estimation through chest organ segmentation, however, requires large amounts of pixel-level annotated data, which is often unavailable. To alleviate this problem, we propose an unsupervised domain adaptation framework based on adversarial networks. The framework learns dom"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.03434","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":"1807.03434","created_at":"2026-05-18T00:11:10.440732+00:00"},{"alias_kind":"arxiv_version","alias_value":"1807.03434v1","created_at":"2026-05-18T00:11:10.440732+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.03434","created_at":"2026-05-18T00:11:10.440732+00:00"},{"alias_kind":"pith_short_12","alias_value":"DHXHXE6JCPUU","created_at":"2026-05-18T12:32:19.392346+00:00"},{"alias_kind":"pith_short_16","alias_value":"DHXHXE6JCPUUBGOZ","created_at":"2026-05-18T12:32:19.392346+00:00"},{"alias_kind":"pith_short_8","alias_value":"DHXHXE6J","created_at":"2026-05-18T12:32:19.392346+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/DHXHXE6JCPUUBGOZQQ2CEO52EI","json":"https://pith.science/pith/DHXHXE6JCPUUBGOZQQ2CEO52EI.json","graph_json":"https://pith.science/api/pith-number/DHXHXE6JCPUUBGOZQQ2CEO52EI/graph.json","events_json":"https://pith.science/api/pith-number/DHXHXE6JCPUUBGOZQQ2CEO52EI/events.json","paper":"https://pith.science/paper/DHXHXE6J"},"agent_actions":{"view_html":"https://pith.science/pith/DHXHXE6JCPUUBGOZQQ2CEO52EI","download_json":"https://pith.science/pith/DHXHXE6JCPUUBGOZQQ2CEO52EI.json","view_paper":"https://pith.science/paper/DHXHXE6J","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1807.03434&json=true","fetch_graph":"https://pith.science/api/pith-number/DHXHXE6JCPUUBGOZQQ2CEO52EI/graph.json","fetch_events":"https://pith.science/api/pith-number/DHXHXE6JCPUUBGOZQQ2CEO52EI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DHXHXE6JCPUUBGOZQQ2CEO52EI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DHXHXE6JCPUUBGOZQQ2CEO52EI/action/storage_attestation","attest_author":"https://pith.science/pith/DHXHXE6JCPUUBGOZQQ2CEO52EI/action/author_attestation","sign_citation":"https://pith.science/pith/DHXHXE6JCPUUBGOZQQ2CEO52EI/action/citation_signature","submit_replication":"https://pith.science/pith/DHXHXE6JCPUUBGOZQQ2CEO52EI/action/replication_record"}},"created_at":"2026-05-18T00:11:10.440732+00:00","updated_at":"2026-05-18T00:11:10.440732+00:00"}