{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:LLFFT4L6JNZHS5Y3EZTRSZU5IM","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":"aa418f8cd12c3e175a108130de63afa7be31362503495aca034c0f438e02d35e","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2023-03-16T11:16:02Z","title_canon_sha256":"a77db6e1dbcca4db616be81a6b58676598f013bebcd2aab720af09116c3ba143"},"schema_version":"1.0","source":{"id":"2303.09233","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.09233","created_at":"2026-07-05T09:56:19Z"},{"alias_kind":"arxiv_version","alias_value":"2303.09233v3","created_at":"2026-07-05T09:56:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.09233","created_at":"2026-07-05T09:56:19Z"},{"alias_kind":"pith_short_12","alias_value":"LLFFT4L6JNZH","created_at":"2026-07-05T09:56:19Z"},{"alias_kind":"pith_short_16","alias_value":"LLFFT4L6JNZHS5Y3","created_at":"2026-07-05T09:56:19Z"},{"alias_kind":"pith_short_8","alias_value":"LLFFT4L6","created_at":"2026-07-05T09:56:19Z"}],"graph_snapshots":[{"event_id":"sha256:5ab5558c71e6b121e1c37224f4f29ed3bdb95d5cae8c911a7b1b81cb4186023e","target":"graph","created_at":"2026-07-05T09:56:19Z","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/2303.09233/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurately segmenting fluid in 3D optical coherence tomography (OCT) images is critical for detecting eye diseases but remains challenging. Traditional autoencoder-based methods struggle with resolution loss and information recovery. While transformer-based models improve segmentation, they arent optimized for 3D OCT volumes, which vary by vendor and extraction technique. To address this, we propose SwinVFTR, a transformer architecture for precise fluid segmentation in 3D OCT images. SwinVFTR employs channel-wise volumetric sampling and a shifted window transformer block to improve fluid local","authors_text":"Alireza Tavakkoli, George Bebis, Khondker Fariha Hossain, Sal Baker, Sharif Amit Kamran","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2023-03-16T11:16:02Z","title":"SwinVFTR: A Novel Volumetric Feature-learning Transformer for 3D OCT Fluid Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.09233","kind":"arxiv","version":3},"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":"sha256:1aab7f1e96c7e715d43a4a46d3abe29b90f6527eaaa7238512233a89e71d6ece","target":"record","created_at":"2026-07-05T09:56:19Z","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":"aa418f8cd12c3e175a108130de63afa7be31362503495aca034c0f438e02d35e","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2023-03-16T11:16:02Z","title_canon_sha256":"a77db6e1dbcca4db616be81a6b58676598f013bebcd2aab720af09116c3ba143"},"schema_version":"1.0","source":{"id":"2303.09233","kind":"arxiv","version":3}},"canonical_sha256":"5aca59f17e4b7279771b266719669d430cc862d4716e2515b03c1b7844732dac","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5aca59f17e4b7279771b266719669d430cc862d4716e2515b03c1b7844732dac","first_computed_at":"2026-07-05T09:56:19.973503Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:56:19.973503Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qCSz4CUY/IYa5rLjaG6wBlQ0NEiGZew05jgijJ55oqliCYNFh3hCV9FOcfMvsY5SO/Hyxi9FKG1s8M8uOQFXDw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:56:19.973860Z","signed_message":"canonical_sha256_bytes"},"source_id":"2303.09233","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1aab7f1e96c7e715d43a4a46d3abe29b90f6527eaaa7238512233a89e71d6ece","sha256:5ab5558c71e6b121e1c37224f4f29ed3bdb95d5cae8c911a7b1b81cb4186023e"],"state_sha256":"e22f22ab743bc1de6db819084a3240831d9335afaf61d87f53c92c359e86c6d0"}