{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:W5UEVN2A7H3ETS7RBBK2NBPPYS","short_pith_number":"pith:W5UEVN2A","canonical_record":{"source":{"id":"2312.09514","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-15T03:33:08Z","cross_cats_sorted":[],"title_canon_sha256":"7ead144a8564799479a873df9868cd68ce427ec7b6776fcc2f5759cbf3f037b3","abstract_canon_sha256":"0d4e6d6609b62d106a7e9076412e2194528357663a77033aea161afe2197a345"},"schema_version":"1.0"},"canonical_sha256":"b7684ab740f9f649cbf10855a685efc4828fe9cff8dd1b0b1230502bbab1af97","source":{"kind":"arxiv","id":"2312.09514","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.09514","created_at":"2026-07-05T07:24:26Z"},{"alias_kind":"arxiv_version","alias_value":"2312.09514v1","created_at":"2026-07-05T07:24:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.09514","created_at":"2026-07-05T07:24:26Z"},{"alias_kind":"pith_short_12","alias_value":"W5UEVN2A7H3E","created_at":"2026-07-05T07:24:26Z"},{"alias_kind":"pith_short_16","alias_value":"W5UEVN2A7H3ETS7R","created_at":"2026-07-05T07:24:26Z"},{"alias_kind":"pith_short_8","alias_value":"W5UEVN2A","created_at":"2026-07-05T07:24:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:W5UEVN2A7H3ETS7RBBK2NBPPYS","target":"record","payload":{"canonical_record":{"source":{"id":"2312.09514","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-15T03:33:08Z","cross_cats_sorted":[],"title_canon_sha256":"7ead144a8564799479a873df9868cd68ce427ec7b6776fcc2f5759cbf3f037b3","abstract_canon_sha256":"0d4e6d6609b62d106a7e9076412e2194528357663a77033aea161afe2197a345"},"schema_version":"1.0"},"canonical_sha256":"b7684ab740f9f649cbf10855a685efc4828fe9cff8dd1b0b1230502bbab1af97","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:24:26.169352Z","signature_b64":"gZcFPJ2OCDa6oILnBU03tZupGpsT8EaXCJMwM0/1540AJdzlpldbUs9D+phRlrberGkQ/kVMy3RcUHLwh7gxAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b7684ab740f9f649cbf10855a685efc4828fe9cff8dd1b0b1230502bbab1af97","last_reissued_at":"2026-07-05T07:24:26.168827Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:24:26.168827Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2312.09514","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":"2026-07-05T07:24:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9Ar/Oe4a+FdKMXHpwJhFRb4rELhd6u8r47r18RZ7FGAQToQy6Q3crOnDNiEhSoCMx2NZ1/6Hh2Fc4+/02bN1Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-27T14:13:07.439603Z"},"content_sha256":"fcb13d52309cd578f48a27da9214400364bae37cdc40237125ed6d451dad28ea","schema_version":"1.0","event_id":"sha256:fcb13d52309cd578f48a27da9214400364bae37cdc40237125ed6d451dad28ea"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:W5UEVN2A7H3ETS7RBBK2NBPPYS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Single PW takes a shortcut to compound PW in US imaging","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hengrong Lan, Jianwen Luo, Lijie Huang, Qiong He, Zhiqiang Li","submitted_at":"2023-12-15T03:33:08Z","abstract_excerpt":"Reconstruction of ultrasound (US) images from radio-frequency data can be conceptualized as a linear inverse problem. Traditional deep learning approaches, which aim to improve the quality of US images by directly learning priors, often encounter challenges in generalization. Recently, diffusion-based generative models have received significant attention within the research community due to their robust performance in image reconstruction tasks. However, a limitation of these models is their inherent low speed in generating image samples from pure Gaussian noise progressively. In this study, w"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.09514","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/2312.09514/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":"2026-07-05T07:24:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"U3sbPFcdfDhmN3MbLtu3KEGUXewEo2IHQrnJsSotU1cZZVQAyJoBaDP+PcxBp91By7nZIVbbfALJbMd4LbB+Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-27T14:13:07.439963Z"},"content_sha256":"d12bdc67dc076feacd9d59190797259d3748c1258475e789103217cf6a218e1b","schema_version":"1.0","event_id":"sha256:d12bdc67dc076feacd9d59190797259d3748c1258475e789103217cf6a218e1b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/W5UEVN2A7H3ETS7RBBK2NBPPYS/bundle.json","state_url":"https://pith.science/pith/W5UEVN2A7H3ETS7RBBK2NBPPYS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/W5UEVN2A7H3ETS7RBBK2NBPPYS/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":"2026-07-27T14:13:07Z","links":{"resolver":"https://pith.science/pith/W5UEVN2A7H3ETS7RBBK2NBPPYS","bundle":"https://pith.science/pith/W5UEVN2A7H3ETS7RBBK2NBPPYS/bundle.json","state":"https://pith.science/pith/W5UEVN2A7H3ETS7RBBK2NBPPYS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/W5UEVN2A7H3ETS7RBBK2NBPPYS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:W5UEVN2A7H3ETS7RBBK2NBPPYS","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":"0d4e6d6609b62d106a7e9076412e2194528357663a77033aea161afe2197a345","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-15T03:33:08Z","title_canon_sha256":"7ead144a8564799479a873df9868cd68ce427ec7b6776fcc2f5759cbf3f037b3"},"schema_version":"1.0","source":{"id":"2312.09514","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.09514","created_at":"2026-07-05T07:24:26Z"},{"alias_kind":"arxiv_version","alias_value":"2312.09514v1","created_at":"2026-07-05T07:24:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.09514","created_at":"2026-07-05T07:24:26Z"},{"alias_kind":"pith_short_12","alias_value":"W5UEVN2A7H3E","created_at":"2026-07-05T07:24:26Z"},{"alias_kind":"pith_short_16","alias_value":"W5UEVN2A7H3ETS7R","created_at":"2026-07-05T07:24:26Z"},{"alias_kind":"pith_short_8","alias_value":"W5UEVN2A","created_at":"2026-07-05T07:24:26Z"}],"graph_snapshots":[{"event_id":"sha256:d12bdc67dc076feacd9d59190797259d3748c1258475e789103217cf6a218e1b","target":"graph","created_at":"2026-07-05T07:24:26Z","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/2312.09514/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Reconstruction of ultrasound (US) images from radio-frequency data can be conceptualized as a linear inverse problem. Traditional deep learning approaches, which aim to improve the quality of US images by directly learning priors, often encounter challenges in generalization. Recently, diffusion-based generative models have received significant attention within the research community due to their robust performance in image reconstruction tasks. However, a limitation of these models is their inherent low speed in generating image samples from pure Gaussian noise progressively. In this study, w","authors_text":"Hengrong Lan, Jianwen Luo, Lijie Huang, Qiong He, Zhiqiang Li","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-15T03:33:08Z","title":"Single PW takes a shortcut to compound PW in US imaging"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.09514","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:fcb13d52309cd578f48a27da9214400364bae37cdc40237125ed6d451dad28ea","target":"record","created_at":"2026-07-05T07:24:26Z","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":"0d4e6d6609b62d106a7e9076412e2194528357663a77033aea161afe2197a345","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-15T03:33:08Z","title_canon_sha256":"7ead144a8564799479a873df9868cd68ce427ec7b6776fcc2f5759cbf3f037b3"},"schema_version":"1.0","source":{"id":"2312.09514","kind":"arxiv","version":1}},"canonical_sha256":"b7684ab740f9f649cbf10855a685efc4828fe9cff8dd1b0b1230502bbab1af97","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b7684ab740f9f649cbf10855a685efc4828fe9cff8dd1b0b1230502bbab1af97","first_computed_at":"2026-07-05T07:24:26.168827Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:24:26.168827Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gZcFPJ2OCDa6oILnBU03tZupGpsT8EaXCJMwM0/1540AJdzlpldbUs9D+phRlrberGkQ/kVMy3RcUHLwh7gxAA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:24:26.169352Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.09514","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fcb13d52309cd578f48a27da9214400364bae37cdc40237125ed6d451dad28ea","sha256:d12bdc67dc076feacd9d59190797259d3748c1258475e789103217cf6a218e1b"],"state_sha256":"c3ccab850f1de80fa5a32f45293b55e41974cf011a652c7949f90ad283e80207"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xcNLej/zRN24k3db5lO82bpC5lC+76vBDbYqvYtqnXAShxt5wkq3+ryn5rrfJFnkq2JOMjA9m52RJRgwcY/oBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-27T14:13:07.442430Z","bundle_sha256":"58213e149cf00b7d4cf77e35c49516b357f3d685091ad4647bed2aaa97132983"}}