{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:WAXSBFUGD2DK6EEB6IDAF6APP6","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"99574c66191ad63836a8321fbb235104426f4ecc317bd753c442c53711965798","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2023-01-31T14:46:16Z","title_canon_sha256":"0475d075fdc018612ed0b59fb8513cc131a03630c455588b87fccdc26fe57d93"},"schema_version":"1.0","source":{"id":"2301.13674","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.13674","created_at":"2026-07-05T05:37:17Z"},{"alias_kind":"arxiv_version","alias_value":"2301.13674v1","created_at":"2026-07-05T05:37:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.13674","created_at":"2026-07-05T05:37:17Z"},{"alias_kind":"pith_short_12","alias_value":"WAXSBFUGD2DK","created_at":"2026-07-05T05:37:17Z"},{"alias_kind":"pith_short_16","alias_value":"WAXSBFUGD2DK6EEB","created_at":"2026-07-05T05:37:17Z"},{"alias_kind":"pith_short_8","alias_value":"WAXSBFUG","created_at":"2026-07-05T05:37:17Z"}],"graph_snapshots":[{"event_id":"sha256:d9436282875adeb0692b41e6d70c00f7841749f36585636936f2ad95636d6a25","target":"graph","created_at":"2026-07-05T05:37:17Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2301.13674/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Purpose: Automated distinct bone segmentation from CT scans is widely used in planning and navigation workflows. U-Net variants are known to provide excellent results in supervised semantic segmentation. However, in distinct bone segmentation from upper body CTs a large field of view and a computationally taxing 3D architecture are required. This leads to low-resolution results lacking detail or localisation errors due to missing spatial context when using high-resolution inputs.\n  Methods: We propose to solve this problem by using end-to-end trainable segmentation networks that combine severa","authors_text":"Antal Huck, Eva Schnider, Georg Rauter, Julia Wolleb, Magdalena M\\\"uller-Gerbl, Mireille Toranelli, Philippe C. Cattin","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2023-01-31T14:46:16Z","title":"Improved distinct bone segmentation in upper-body CT through multi-resolution networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.13674","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:46393cd5fce06db588c647b09beb7494c9bb23c1486d909bad0744abbb07633c","target":"record","created_at":"2026-07-05T05:37:17Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"99574c66191ad63836a8321fbb235104426f4ecc317bd753c442c53711965798","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2023-01-31T14:46:16Z","title_canon_sha256":"0475d075fdc018612ed0b59fb8513cc131a03630c455588b87fccdc26fe57d93"},"schema_version":"1.0","source":{"id":"2301.13674","kind":"arxiv","version":1}},"canonical_sha256":"b02f2096861e86af1081f20602f80f7f9909582930846b2506451c068141aeee","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b02f2096861e86af1081f20602f80f7f9909582930846b2506451c068141aeee","first_computed_at":"2026-07-05T05:37:17.468965Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:37:17.468965Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VhtQYzp+CzN1D+Em9+Pl4XJkgcChqkKqpcJGKBWoluCDtgWDw3OIPqO3rmCng7QAbFDMQYy0Zw1RFJWnQEUkDg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:37:17.469971Z","signed_message":"canonical_sha256_bytes"},"source_id":"2301.13674","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:46393cd5fce06db588c647b09beb7494c9bb23c1486d909bad0744abbb07633c","sha256:d9436282875adeb0692b41e6d70c00f7841749f36585636936f2ad95636d6a25"],"state_sha256":"807305cdcada4f633783a68235225bcf47eca30159be6e5094cfea9ebe66890c"}