{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:YDLWUCGYT2KUUEBTGDRJTSTURS","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":"9bba8e9f313709d18b59461248fb4f6fd16b4f9ee92574fdce72d773fd7a7ddd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-08-15T18:18:37Z","title_canon_sha256":"ed8b7064da0cfbe18059982d295ec8bc995763bd11abbefc2a84afaf69cc5018"},"schema_version":"1.0","source":{"id":"1908.05698","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.05698","created_at":"2026-07-04T23:57:52Z"},{"alias_kind":"arxiv_version","alias_value":"1908.05698v1","created_at":"2026-07-04T23:57:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.05698","created_at":"2026-07-04T23:57:52Z"},{"alias_kind":"pith_short_12","alias_value":"YDLWUCGYT2KU","created_at":"2026-07-04T23:57:52Z"},{"alias_kind":"pith_short_16","alias_value":"YDLWUCGYT2KUUEBT","created_at":"2026-07-04T23:57:52Z"},{"alias_kind":"pith_short_8","alias_value":"YDLWUCGY","created_at":"2026-07-04T23:57:52Z"}],"graph_snapshots":[{"event_id":"sha256:c90314b4727e54d700964917e90ffaff77a0366dcbd5130532781d601951b1e0","target":"graph","created_at":"2026-07-04T23:57:52Z","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/1908.05698/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We evaluate a new approach for achieving diffusion MRI data with high spatial resolution, large volume coverage, and fast acquisition speed.\n  A recent method called gSlider-SMS enables whole-brain sub-millimeter diffusion MRI with high signal-to-noise ratio (SNR) efficiency. However, despite the efficient acquisition, the resulting images can still suffer from low SNR due to the small size of the imaging voxels. This work proposes to mitigate the SNR problem by combining gSlider-SMS with a regularized SNR-enhancing reconstruction approach.\n  Illustrative results show that, from gSlider-SMS da","authors_text":"Justin P. Haldar, Kawin Setsompop, Qiuyun Fan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-08-15T18:18:37Z","title":"Fast Sub-millimeter Diffusion MRI using gSlider-SMS and SNR-Enhancing Joint Reconstruction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.05698","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":"sha256:0e06ac7bc4d402ffe428575a328d04ce110b291cfa08f27763138a5bce83f700","target":"record","created_at":"2026-07-04T23:57:52Z","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":"9bba8e9f313709d18b59461248fb4f6fd16b4f9ee92574fdce72d773fd7a7ddd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-08-15T18:18:37Z","title_canon_sha256":"ed8b7064da0cfbe18059982d295ec8bc995763bd11abbefc2a84afaf69cc5018"},"schema_version":"1.0","source":{"id":"1908.05698","kind":"arxiv","version":1}},"canonical_sha256":"c0d76a08d89e954a103330e299ca748ca787628fb7c90559e7a353a5024f55d6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c0d76a08d89e954a103330e299ca748ca787628fb7c90559e7a353a5024f55d6","first_computed_at":"2026-07-04T23:57:52.485147Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-04T23:57:52.485147Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MLL7DDgmtUIFPP23SCBgLxxmsOpkppYshh9MinyAfKWZB/s7mW2HABz0qEDktrBiJyIoXxHDQxmDkMo3AUwNCw==","signature_status":"signed_v1","signed_at":"2026-07-04T23:57:52.485518Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.05698","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0e06ac7bc4d402ffe428575a328d04ce110b291cfa08f27763138a5bce83f700","sha256:c90314b4727e54d700964917e90ffaff77a0366dcbd5130532781d601951b1e0"],"state_sha256":"4cda67aab63f506faeff9a078cc96081f643d03cef6fe91a525e39fa592d0461"}