{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:IK5BBAOM7YDT6LBFDYRNV6C46L","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":"0012e32f7067cdf4a6b3efa86673a8b12f1d32ab392726e5c7488022e42416dd","cross_cats_sorted":["cs.LG","eess.IV"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-07-03T20:39:48Z","title_canon_sha256":"cbb219b85af00efe68980fd412d45dd6f50ad2ed72917c6b672e7207e1b5da70"},"schema_version":"1.0","source":{"id":"2307.01346","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.01346","created_at":"2026-07-05T06:27:55Z"},{"alias_kind":"arxiv_version","alias_value":"2307.01346v1","created_at":"2026-07-05T06:27:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.01346","created_at":"2026-07-05T06:27:55Z"},{"alias_kind":"pith_short_12","alias_value":"IK5BBAOM7YDT","created_at":"2026-07-05T06:27:55Z"},{"alias_kind":"pith_short_16","alias_value":"IK5BBAOM7YDT6LBF","created_at":"2026-07-05T06:27:55Z"},{"alias_kind":"pith_short_8","alias_value":"IK5BBAOM","created_at":"2026-07-05T06:27:55Z"}],"graph_snapshots":[{"event_id":"sha256:55b8c779352b7f3029f1a6c5418831114bd6d030361f831f91f1122334b91643","target":"graph","created_at":"2026-07-05T06:27:55Z","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/2307.01346/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose a new method, Patch-CNN, for diffusion tensor (DT) estimation from only six-direction diffusion weighted images (DWI). Deep learning-based methods have been recently proposed for dMRI parameter estimation, using either voxel-wise fully-connected neural networks (FCN) or image-wise convolutional neural networks (CNN). In the acute clinical context -- where pressure of time limits the number of imaged directions to a minimum -- existing approaches either require an infeasible number of training images volumes (image-wise CNNs), or do not estimate the fibre orientations (voxel-wise FCN","authors_text":"Hui Zhang, Parashkev Nachev, Robert Gray, Ting Gong, Tobias Goodwin-Allcock","cross_cats":["cs.LG","eess.IV"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-07-03T20:39:48Z","title":"Patch-CNN: Training data-efficient deep learning for high-fidelity diffusion tensor estimation from minimal diffusion protocols"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.01346","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":"sha256:0e92b98b1e840675aaff4d6b1f66330c721acba379da64e1c52241754f9dabb2","target":"record","created_at":"2026-07-05T06:27:55Z","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":"0012e32f7067cdf4a6b3efa86673a8b12f1d32ab392726e5c7488022e42416dd","cross_cats_sorted":["cs.LG","eess.IV"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-07-03T20:39:48Z","title_canon_sha256":"cbb219b85af00efe68980fd412d45dd6f50ad2ed72917c6b672e7207e1b5da70"},"schema_version":"1.0","source":{"id":"2307.01346","kind":"arxiv","version":1}},"canonical_sha256":"42ba1081ccfe073f2c251e22daf85cf2f8950555e5b1353b0fb1ae90558ac774","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"42ba1081ccfe073f2c251e22daf85cf2f8950555e5b1353b0fb1ae90558ac774","first_computed_at":"2026-07-05T06:27:55.206543Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:27:55.206543Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QIg2uUxEGo0GTJjlOrPcsjDzWLAiSCRr60kYJlu1n5cwwnORKvOWfStTAQUtTPbqvDhCsrqDcqLdRUGrBcRYCw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:27:55.207003Z","signed_message":"canonical_sha256_bytes"},"source_id":"2307.01346","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0e92b98b1e840675aaff4d6b1f66330c721acba379da64e1c52241754f9dabb2","sha256:55b8c779352b7f3029f1a6c5418831114bd6d030361f831f91f1122334b91643"],"state_sha256":"f320570e2dffe28d27bf22981deab2dc1bc5ab11d23f5dccaa2955209b0cacfd"}