{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2011:YLVRLFR3DLXSBFEL2HIEEF4M6Y","short_pith_number":"pith:YLVRLFR3","schema_version":"1.0","canonical_sha256":"c2eb15963b1aef20948bd1d042178cf602a1d4818fa36b7cd3d738b05fe0d67d","source":{"kind":"arxiv","id":"1103.3532","version":1},"attestation_state":"computed","paper":{"title":"4D Wavelet-Based Regularization for Parallel MRI Reconstruction: Impact on Subject and Group-Levels Statistical Sensitivity in fMRI","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","physics.med-ph"],"primary_cat":"stat.ME","authors_text":"Jean-Christophe Pesquet, Lotfi Chaari, Philippe Ciuciu, S\\'ebastien M\\'eriaux, Solveig Badillo","submitted_at":"2011-03-17T23:11:58Z","abstract_excerpt":"Parallel MRI is a fast imaging technique that enables the acquisition of highly resolved images in space. It relies on $k$-space undersampling and multiple receiver coils with complementary sensitivity profiles in order to reconstruct a full Field-Of-View (FOV) image. The performance of parallel imaging mainly depends on the reconstruction algorithm, which can proceed either in the original $k$-space (GRAPPA, SMASH) or in the image domain (SENSE-like methods). To improve the performance of the widely used SENSE algorithm, 2D- or slice-specific regularization in the wavelet domain has been effi"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1103.3532","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2011-03-17T23:11:58Z","cross_cats_sorted":["cs.CV","physics.med-ph"],"title_canon_sha256":"a7261239f306e24495a9b03d450b01d7d3150c48555fa2deb6629886558ea61c","abstract_canon_sha256":"c39b09c6611bc79fbfeef41d45277123a061d41c2e033f088cdb6ba6241459a8"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:26:32.442661Z","signature_b64":"jilRVsaLl0VmpoJh2qkwzoxZbFsVB0kMwEZtsUKuK4PK994rbdd+R0K6wDEuVKRPesY+QOIQd3pA+fWinR55DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c2eb15963b1aef20948bd1d042178cf602a1d4818fa36b7cd3d738b05fe0d67d","last_reissued_at":"2026-05-18T04:26:32.442106Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:26:32.442106Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"4D Wavelet-Based Regularization for Parallel MRI Reconstruction: Impact on Subject and Group-Levels Statistical Sensitivity in fMRI","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","physics.med-ph"],"primary_cat":"stat.ME","authors_text":"Jean-Christophe Pesquet, Lotfi Chaari, Philippe Ciuciu, S\\'ebastien M\\'eriaux, Solveig Badillo","submitted_at":"2011-03-17T23:11:58Z","abstract_excerpt":"Parallel MRI is a fast imaging technique that enables the acquisition of highly resolved images in space. It relies on $k$-space undersampling and multiple receiver coils with complementary sensitivity profiles in order to reconstruct a full Field-Of-View (FOV) image. The performance of parallel imaging mainly depends on the reconstruction algorithm, which can proceed either in the original $k$-space (GRAPPA, SMASH) or in the image domain (SENSE-like methods). To improve the performance of the widely used SENSE algorithm, 2D- or slice-specific regularization in the wavelet domain has been effi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1103.3532","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":""},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1103.3532","created_at":"2026-05-18T04:26:32.442178+00:00"},{"alias_kind":"arxiv_version","alias_value":"1103.3532v1","created_at":"2026-05-18T04:26:32.442178+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1103.3532","created_at":"2026-05-18T04:26:32.442178+00:00"},{"alias_kind":"pith_short_12","alias_value":"YLVRLFR3DLXS","created_at":"2026-05-18T12:26:47.523578+00:00"},{"alias_kind":"pith_short_16","alias_value":"YLVRLFR3DLXSBFEL","created_at":"2026-05-18T12:26:47.523578+00:00"},{"alias_kind":"pith_short_8","alias_value":"YLVRLFR3","created_at":"2026-05-18T12:26:47.523578+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/YLVRLFR3DLXSBFEL2HIEEF4M6Y","json":"https://pith.science/pith/YLVRLFR3DLXSBFEL2HIEEF4M6Y.json","graph_json":"https://pith.science/api/pith-number/YLVRLFR3DLXSBFEL2HIEEF4M6Y/graph.json","events_json":"https://pith.science/api/pith-number/YLVRLFR3DLXSBFEL2HIEEF4M6Y/events.json","paper":"https://pith.science/paper/YLVRLFR3"},"agent_actions":{"view_html":"https://pith.science/pith/YLVRLFR3DLXSBFEL2HIEEF4M6Y","download_json":"https://pith.science/pith/YLVRLFR3DLXSBFEL2HIEEF4M6Y.json","view_paper":"https://pith.science/paper/YLVRLFR3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1103.3532&json=true","fetch_graph":"https://pith.science/api/pith-number/YLVRLFR3DLXSBFEL2HIEEF4M6Y/graph.json","fetch_events":"https://pith.science/api/pith-number/YLVRLFR3DLXSBFEL2HIEEF4M6Y/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YLVRLFR3DLXSBFEL2HIEEF4M6Y/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YLVRLFR3DLXSBFEL2HIEEF4M6Y/action/storage_attestation","attest_author":"https://pith.science/pith/YLVRLFR3DLXSBFEL2HIEEF4M6Y/action/author_attestation","sign_citation":"https://pith.science/pith/YLVRLFR3DLXSBFEL2HIEEF4M6Y/action/citation_signature","submit_replication":"https://pith.science/pith/YLVRLFR3DLXSBFEL2HIEEF4M6Y/action/replication_record"}},"created_at":"2026-05-18T04:26:32.442178+00:00","updated_at":"2026-05-18T04:26:32.442178+00:00"}