{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:HFVVRZPEFXVQZLLCJPREFPC7QZ","short_pith_number":"pith:HFVVRZPE","schema_version":"1.0","canonical_sha256":"396b58e5e42deb0cad624be242bc5f867101bd933cb4a9a0219bdbc10c852f45","source":{"kind":"arxiv","id":"2111.01397","version":2},"attestation_state":"computed","paper":{"title":"Sensitivity Analysis for Optimizing Electrical Impedance Tomography Protocols","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"physics.med-ph","authors_text":"Can Aygen, Charles Costakis, Chulin Wang, Claire Onsager, Lauren Lang, Matthew A. Grayson, Suzan van der Lee","submitted_at":"2021-11-02T07:15:38Z","abstract_excerpt":"Electrical impedance tomography (EIT) is a noninvasive imaging method whereby electrical measurements on the boundary of a conductive medium (the data) are taken according to a prescribed protocol set and inverted to map the internal conductivity (the model). This paper introduces a sensitivity analysis method and corresponding inversion and protocol optimization that generalizes the criteria for tomographic inversion to minimize the model-space dimensionality and maximize data importance. Sensitivity vectors, defined as rows of the Jacobian matrix in the linearized forward problem, are used t"},"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":"2111.01397","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.med-ph","submitted_at":"2021-11-02T07:15:38Z","cross_cats_sorted":[],"title_canon_sha256":"91593f9d1c11bf7192bd87dfa0c67f424e90ac54ba64126300e7149f9db9c1ca","abstract_canon_sha256":"b90da6d00d71635276e0b3f666835c7779736663130bf16167ef569920f1573b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:33:09.267688Z","signature_b64":"OGAb6RWfhF2u2QDrf9R8VXmZUPXzCMhv2Dy4qyhmjUPUgLja1h6ySQL4+bp3WtZRGG1V7Q7pw4TmDtuW/4cDDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"396b58e5e42deb0cad624be242bc5f867101bd933cb4a9a0219bdbc10c852f45","last_reissued_at":"2026-07-05T03:33:09.267271Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:33:09.267271Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Sensitivity Analysis for Optimizing Electrical Impedance Tomography Protocols","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"physics.med-ph","authors_text":"Can Aygen, Charles Costakis, Chulin Wang, Claire Onsager, Lauren Lang, Matthew A. Grayson, Suzan van der Lee","submitted_at":"2021-11-02T07:15:38Z","abstract_excerpt":"Electrical impedance tomography (EIT) is a noninvasive imaging method whereby electrical measurements on the boundary of a conductive medium (the data) are taken according to a prescribed protocol set and inverted to map the internal conductivity (the model). This paper introduces a sensitivity analysis method and corresponding inversion and protocol optimization that generalizes the criteria for tomographic inversion to minimize the model-space dimensionality and maximize data importance. Sensitivity vectors, defined as rows of the Jacobian matrix in the linearized forward problem, are used t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.01397","kind":"arxiv","version":2},"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/2111.01397/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2111.01397","created_at":"2026-07-05T03:33:09.267342+00:00"},{"alias_kind":"arxiv_version","alias_value":"2111.01397v2","created_at":"2026-07-05T03:33:09.267342+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.01397","created_at":"2026-07-05T03:33:09.267342+00:00"},{"alias_kind":"pith_short_12","alias_value":"HFVVRZPEFXVQ","created_at":"2026-07-05T03:33:09.267342+00:00"},{"alias_kind":"pith_short_16","alias_value":"HFVVRZPEFXVQZLLC","created_at":"2026-07-05T03:33:09.267342+00:00"},{"alias_kind":"pith_short_8","alias_value":"HFVVRZPE","created_at":"2026-07-05T03:33:09.267342+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/HFVVRZPEFXVQZLLCJPREFPC7QZ","json":"https://pith.science/pith/HFVVRZPEFXVQZLLCJPREFPC7QZ.json","graph_json":"https://pith.science/api/pith-number/HFVVRZPEFXVQZLLCJPREFPC7QZ/graph.json","events_json":"https://pith.science/api/pith-number/HFVVRZPEFXVQZLLCJPREFPC7QZ/events.json","paper":"https://pith.science/paper/HFVVRZPE"},"agent_actions":{"view_html":"https://pith.science/pith/HFVVRZPEFXVQZLLCJPREFPC7QZ","download_json":"https://pith.science/pith/HFVVRZPEFXVQZLLCJPREFPC7QZ.json","view_paper":"https://pith.science/paper/HFVVRZPE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2111.01397&json=true","fetch_graph":"https://pith.science/api/pith-number/HFVVRZPEFXVQZLLCJPREFPC7QZ/graph.json","fetch_events":"https://pith.science/api/pith-number/HFVVRZPEFXVQZLLCJPREFPC7QZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HFVVRZPEFXVQZLLCJPREFPC7QZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HFVVRZPEFXVQZLLCJPREFPC7QZ/action/storage_attestation","attest_author":"https://pith.science/pith/HFVVRZPEFXVQZLLCJPREFPC7QZ/action/author_attestation","sign_citation":"https://pith.science/pith/HFVVRZPEFXVQZLLCJPREFPC7QZ/action/citation_signature","submit_replication":"https://pith.science/pith/HFVVRZPEFXVQZLLCJPREFPC7QZ/action/replication_record"}},"created_at":"2026-07-05T03:33:09.267342+00:00","updated_at":"2026-07-05T03:33:09.267342+00:00"}