{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:HIRRB3FOKWACE2J2HFXDCJYUWO","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":"023f2cf5d5572312d3ea2df1c7a8affea7a8ac951b0223c9cac9ff477bd4c9df","cross_cats_sorted":["eess.SP","math.OC","physics.med-ph","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-19T15:10:59Z","title_canon_sha256":"f595737cd4d0c63a041fdbb04cd2f29523ff9b4e8911f66414c8fc87c00fa14d"},"schema_version":"1.0","source":{"id":"1906.08143","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.08143","created_at":"2026-07-05T00:02:27Z"},{"alias_kind":"arxiv_version","alias_value":"1906.08143v4","created_at":"2026-07-05T00:02:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.08143","created_at":"2026-07-05T00:02:27Z"},{"alias_kind":"pith_short_12","alias_value":"HIRRB3FOKWAC","created_at":"2026-07-05T00:02:27Z"},{"alias_kind":"pith_short_16","alias_value":"HIRRB3FOKWACE2J2","created_at":"2026-07-05T00:02:27Z"},{"alias_kind":"pith_short_8","alias_value":"HIRRB3FO","created_at":"2026-07-05T00:02:27Z"}],"graph_snapshots":[{"event_id":"sha256:958c5096eb0a89115ce8811757d59efd3359dba0b226ff3199ff5f16bdc2fb90","target":"graph","created_at":"2026-07-05T00:02:27Z","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/1906.08143/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Medical imaging is playing a more and more important role in clinics. However, there are several issues in different imaging modalities such as slow imaging speed in MRI, radiation injury in CT and PET. Therefore, accelerating MRI, reducing radiation dose in CT and PET have been ongoing research topics since their invention. Usually, acquiring less data is a direct but important strategy to address these issues. However, less acquisition usually results in aliasing artifacts in reconstructions. Recently, deep learning (DL) has been introduced in medical image reconstruction and shown potential","authors_text":"Dong Liang, HaiFeng Wang, Hairong Zheng, Jianwei Chen, Jing Cheng, Leslie Ying, Qiegen Liu, Qiyang Zhang, Ting Su, Xin Liu, Yanjie Zhu, Yongshuai Ge, Zhanli Hu","cross_cats":["eess.SP","math.OC","physics.med-ph","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-19T15:10:59Z","title":"Model-based Deep Medical Imaging: the roadmap of generalizing iterative reconstruction model using deep learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.08143","kind":"arxiv","version":4},"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:dfff84ffa64a9c320ecf910d416c10ba74918d95b7ab12b2b3f1cc7638f980d1","target":"record","created_at":"2026-07-05T00:02:27Z","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":"023f2cf5d5572312d3ea2df1c7a8affea7a8ac951b0223c9cac9ff477bd4c9df","cross_cats_sorted":["eess.SP","math.OC","physics.med-ph","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-06-19T15:10:59Z","title_canon_sha256":"f595737cd4d0c63a041fdbb04cd2f29523ff9b4e8911f66414c8fc87c00fa14d"},"schema_version":"1.0","source":{"id":"1906.08143","kind":"arxiv","version":4}},"canonical_sha256":"3a2310ecae558022693a396e312714b38016a4c191e7b59b93f3db0d74f48391","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3a2310ecae558022693a396e312714b38016a4c191e7b59b93f3db0d74f48391","first_computed_at":"2026-07-05T00:02:27.658494Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:02:27.658494Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9TbFDjW+myV6aKWHglKM+1Lf/ehJV7fmhAjhtRFdXT6a79LSlAZEel4kI9O2JgyHFUrzWgTz0Kq6y+eFXFJICw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:02:27.658941Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.08143","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dfff84ffa64a9c320ecf910d416c10ba74918d95b7ab12b2b3f1cc7638f980d1","sha256:958c5096eb0a89115ce8811757d59efd3359dba0b226ff3199ff5f16bdc2fb90"],"state_sha256":"bbe404ae0d054d4c0dd667b8d021d0e15a303cae9f158b3f34be85c5c3895367"}