{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:GKWVAFWZZIUSTKCNT6LDXL6VSF","short_pith_number":"pith:GKWVAFWZ","canonical_record":{"source":{"id":"2107.04938","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-07-11T01:36:57Z","cross_cats_sorted":[],"title_canon_sha256":"87193305c50fb26b57b4ceb9aeb6b076f0c5b30ebc8ce7676a00bd4c9063a647","abstract_canon_sha256":"3773a605538117d18f80ced0c1348096a058704d5acb222a1600184a4f624e99"},"schema_version":"1.0"},"canonical_sha256":"32ad5016d9ca2929a84d9f963bafd5917e384274a4117402addd4c1c81a2f20a","source":{"kind":"arxiv","id":"2107.04938","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2107.04938","created_at":"2026-07-05T02:56:44Z"},{"alias_kind":"arxiv_version","alias_value":"2107.04938v1","created_at":"2026-07-05T02:56:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.04938","created_at":"2026-07-05T02:56:44Z"},{"alias_kind":"pith_short_12","alias_value":"GKWVAFWZZIUS","created_at":"2026-07-05T02:56:44Z"},{"alias_kind":"pith_short_16","alias_value":"GKWVAFWZZIUSTKCN","created_at":"2026-07-05T02:56:44Z"},{"alias_kind":"pith_short_8","alias_value":"GKWVAFWZ","created_at":"2026-07-05T02:56:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:GKWVAFWZZIUSTKCNT6LDXL6VSF","target":"record","payload":{"canonical_record":{"source":{"id":"2107.04938","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-07-11T01:36:57Z","cross_cats_sorted":[],"title_canon_sha256":"87193305c50fb26b57b4ceb9aeb6b076f0c5b30ebc8ce7676a00bd4c9063a647","abstract_canon_sha256":"3773a605538117d18f80ced0c1348096a058704d5acb222a1600184a4f624e99"},"schema_version":"1.0"},"canonical_sha256":"32ad5016d9ca2929a84d9f963bafd5917e384274a4117402addd4c1c81a2f20a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:56:44.476775Z","signature_b64":"2LSvQ9/isOBsP/ND+bq1QnPzWEmAWaUoZjOEeaO2RvmyRIplqbveHUlEUixX/vavSQ9azyUM4CzNXjuh7ngPBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"32ad5016d9ca2929a84d9f963bafd5917e384274a4117402addd4c1c81a2f20a","last_reissued_at":"2026-07-05T02:56:44.476373Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:56:44.476373Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2107.04938","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:56:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TRCAN2OoH349LJ9j1B1E+4joMh6aIgt6+PZjniiUi8CUzvp9ZnL2sHJcKIguZeKyNo3AWlLK/sp0FvW20qqACA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T19:49:54.366558Z"},"content_sha256":"35df9bf671e85a9f6efbae4f365a33f429ba16b0a9c889ec357c820a1fa29af3","schema_version":"1.0","event_id":"sha256:35df9bf671e85a9f6efbae4f365a33f429ba16b0a9c889ec357c820a1fa29af3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:GKWVAFWZZIUSTKCNT6LDXL6VSF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Fiber Clustering: Anatomically Informed Unsupervised Deep Learning for Fast and Effective White Matter Parcellation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chaoyi Zhang, Fan Zhang, Lauren J. O'Donnell, Nikos Makris, Weidong Cai, Yang Song, Yogesh Rathi, Yuqian Chen","submitted_at":"2021-07-11T01:36:57Z","abstract_excerpt":"White matter fiber clustering (WMFC) enables parcellation of white matter tractography for applications such as disease classification and anatomical tract segmentation. However, the lack of ground truth and the ambiguity of fiber data (the points along a fiber can equivalently be represented in forward or reverse order) pose challenges to this task. We propose a novel WMFC framework based on unsupervised deep learning. We solve the unsupervised clustering problem as a self-supervised learning task. Specifically, we use a convolutional neural network to learn embeddings of input fibers, using "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.04938","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2107.04938/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:56:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DGexZ8SuEwMwqNO3ZTIzrl1f3v2PBN5eWZk4xs5j0vxI+TH1UvJbwOdtIS5r1Iu9Kl/Zr7CHlzUMtCKZWHEkBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T19:49:54.367060Z"},"content_sha256":"1b4ec99ea593b835f16069787d1068ef51f1e20458c8d1a3221b0f3827afbeae","schema_version":"1.0","event_id":"sha256:1b4ec99ea593b835f16069787d1068ef51f1e20458c8d1a3221b0f3827afbeae"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GKWVAFWZZIUSTKCNT6LDXL6VSF/bundle.json","state_url":"https://pith.science/pith/GKWVAFWZZIUSTKCNT6LDXL6VSF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GKWVAFWZZIUSTKCNT6LDXL6VSF/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-05T19:49:54Z","links":{"resolver":"https://pith.science/pith/GKWVAFWZZIUSTKCNT6LDXL6VSF","bundle":"https://pith.science/pith/GKWVAFWZZIUSTKCNT6LDXL6VSF/bundle.json","state":"https://pith.science/pith/GKWVAFWZZIUSTKCNT6LDXL6VSF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GKWVAFWZZIUSTKCNT6LDXL6VSF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:GKWVAFWZZIUSTKCNT6LDXL6VSF","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":"3773a605538117d18f80ced0c1348096a058704d5acb222a1600184a4f624e99","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-07-11T01:36:57Z","title_canon_sha256":"87193305c50fb26b57b4ceb9aeb6b076f0c5b30ebc8ce7676a00bd4c9063a647"},"schema_version":"1.0","source":{"id":"2107.04938","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2107.04938","created_at":"2026-07-05T02:56:44Z"},{"alias_kind":"arxiv_version","alias_value":"2107.04938v1","created_at":"2026-07-05T02:56:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.04938","created_at":"2026-07-05T02:56:44Z"},{"alias_kind":"pith_short_12","alias_value":"GKWVAFWZZIUS","created_at":"2026-07-05T02:56:44Z"},{"alias_kind":"pith_short_16","alias_value":"GKWVAFWZZIUSTKCN","created_at":"2026-07-05T02:56:44Z"},{"alias_kind":"pith_short_8","alias_value":"GKWVAFWZ","created_at":"2026-07-05T02:56:44Z"}],"graph_snapshots":[{"event_id":"sha256:1b4ec99ea593b835f16069787d1068ef51f1e20458c8d1a3221b0f3827afbeae","target":"graph","created_at":"2026-07-05T02:56:44Z","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/2107.04938/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"White matter fiber clustering (WMFC) enables parcellation of white matter tractography for applications such as disease classification and anatomical tract segmentation. However, the lack of ground truth and the ambiguity of fiber data (the points along a fiber can equivalently be represented in forward or reverse order) pose challenges to this task. We propose a novel WMFC framework based on unsupervised deep learning. We solve the unsupervised clustering problem as a self-supervised learning task. Specifically, we use a convolutional neural network to learn embeddings of input fibers, using ","authors_text":"Chaoyi Zhang, Fan Zhang, Lauren J. O'Donnell, Nikos Makris, Weidong Cai, Yang Song, Yogesh Rathi, Yuqian Chen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-07-11T01:36:57Z","title":"Deep Fiber Clustering: Anatomically Informed Unsupervised Deep Learning for Fast and Effective White Matter Parcellation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.04938","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":"sha256:35df9bf671e85a9f6efbae4f365a33f429ba16b0a9c889ec357c820a1fa29af3","target":"record","created_at":"2026-07-05T02:56:44Z","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":"3773a605538117d18f80ced0c1348096a058704d5acb222a1600184a4f624e99","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-07-11T01:36:57Z","title_canon_sha256":"87193305c50fb26b57b4ceb9aeb6b076f0c5b30ebc8ce7676a00bd4c9063a647"},"schema_version":"1.0","source":{"id":"2107.04938","kind":"arxiv","version":1}},"canonical_sha256":"32ad5016d9ca2929a84d9f963bafd5917e384274a4117402addd4c1c81a2f20a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"32ad5016d9ca2929a84d9f963bafd5917e384274a4117402addd4c1c81a2f20a","first_computed_at":"2026-07-05T02:56:44.476373Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:56:44.476373Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2LSvQ9/isOBsP/ND+bq1QnPzWEmAWaUoZjOEeaO2RvmyRIplqbveHUlEUixX/vavSQ9azyUM4CzNXjuh7ngPBA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:56:44.476775Z","signed_message":"canonical_sha256_bytes"},"source_id":"2107.04938","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:35df9bf671e85a9f6efbae4f365a33f429ba16b0a9c889ec357c820a1fa29af3","sha256:1b4ec99ea593b835f16069787d1068ef51f1e20458c8d1a3221b0f3827afbeae"],"state_sha256":"dbc215410b2ea6ad6672e8b7cbf933d14b0b52b8c83ad540a17af0757fca4a8e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"z4Y/nfTUobk/Ptu7Q4b/PDRk4tTEWez469laS5yyfd6Wu3HZ9iANt+4vvo/yKEipSfslhONFnm/X4c+UTwGmDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T19:49:54.372192Z","bundle_sha256":"b591e717e6671011c657c69c70254af4123bc191d29a5f60b045d494aafcdfe8"}}