{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:6WTHZS7754YTE355VYVGTSQR6P","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":"c2de434b5beef14cee1c04a2afba1969064a4a29ae69ea81dae6c13a13506ba0","cross_cats_sorted":["cs.CV","cs.LG","q-bio.NC","q-bio.QM"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2020-10-07T16:45:55Z","title_canon_sha256":"229ff05a4aabd720e771fc435c33b641f4dc20cee33df8d8db688864c3f9d04e"},"schema_version":"1.0","source":{"id":"2010.04007","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.04007","created_at":"2026-07-05T03:02:09Z"},{"alias_kind":"arxiv_version","alias_value":"2010.04007v2","created_at":"2026-07-05T03:02:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.04007","created_at":"2026-07-05T03:02:09Z"},{"alias_kind":"pith_short_12","alias_value":"6WTHZS7754YT","created_at":"2026-07-05T03:02:09Z"},{"alias_kind":"pith_short_16","alias_value":"6WTHZS7754YTE355","created_at":"2026-07-05T03:02:09Z"},{"alias_kind":"pith_short_8","alias_value":"6WTHZS77","created_at":"2026-07-05T03:02:09Z"}],"graph_snapshots":[{"event_id":"sha256:db035f53540e0c746f85641af2b28b1e6a1e69d61743a755a1e272c92023b13a","target":"graph","created_at":"2026-07-05T03:02:09Z","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/2010.04007/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Current brain white matter fiber tracking techniques show a number of problems, including: generating large proportions of streamlines that do not accurately describe the underlying anatomy; extracting streamlines that are not supported by the underlying diffusion signal; and under-representing some fiber populations, among others. In this paper, we describe a novel autoencoder-based learning method to filter streamlines from diffusion MRI tractography, and hence, to obtain more reliable tractograms. Our method, dubbed FINTA (Filtering in Tractography using Autoencoders) uses raw, unlabeled tr","authors_text":"Carl Lemaire, Fran\\c{c}ois Rheault, Guillaume Theaud, Jon Haitz Legarreta, Laurent Petit, Maxime Descoteaux, Pierre-Marc Jodoin","cross_cats":["cs.CV","cs.LG","q-bio.NC","q-bio.QM"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2020-10-07T16:45:55Z","title":"Filtering in tractography using autoencoders (FINTA)"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.04007","kind":"arxiv","version":2},"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":"sha256:34744a0bfdbf9009a6f572f6d9c3e98dc4e1c8d7ab21aceb2051b7f292a79e44","target":"record","created_at":"2026-07-05T03:02:09Z","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":"c2de434b5beef14cee1c04a2afba1969064a4a29ae69ea81dae6c13a13506ba0","cross_cats_sorted":["cs.CV","cs.LG","q-bio.NC","q-bio.QM"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2020-10-07T16:45:55Z","title_canon_sha256":"229ff05a4aabd720e771fc435c33b641f4dc20cee33df8d8db688864c3f9d04e"},"schema_version":"1.0","source":{"id":"2010.04007","kind":"arxiv","version":2}},"canonical_sha256":"f5a67ccbffef31326fbdae2a69ca11f3d7ae22e84b9f9ecd56a9d542e5e1d42b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f5a67ccbffef31326fbdae2a69ca11f3d7ae22e84b9f9ecd56a9d542e5e1d42b","first_computed_at":"2026-07-05T03:02:09.131778Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:02:09.131778Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"asPeGLLCZJKXVxc0lRfa83Ov3Clp3zHsatcWW8K4zP/Hz0vivuEX/4kvaYrZQVD7OuK0VT1kxPWZKgJVezxyDg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:02:09.132267Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.04007","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:34744a0bfdbf9009a6f572f6d9c3e98dc4e1c8d7ab21aceb2051b7f292a79e44","sha256:db035f53540e0c746f85641af2b28b1e6a1e69d61743a755a1e272c92023b13a"],"state_sha256":"30530f21a3f3ee200859ec1872d946e5693a229306262c0350058b54436427bd"}