{"id":"https://openalex.org/W4386362590","doi":"https://doi.org/10.1109/isbi53787.2023.10230440","title":"Nonlinear Equivariant Imaging: Learning Multi-Parametric Tissue Mapping without Ground Truth for Compressive Quantitative MRI","display_name":"Nonlinear Equivariant Imaging: Learning Multi-Parametric Tissue Mapping without Ground Truth for Compressive Quantitative MRI","publication_year":2023,"publication_date":"2023-04-18","ids":{"openalex":"https://openalex.org/W4386362590","doi":"https://doi.org/10.1109/isbi53787.2023.10230440"},"language":"en","primary_location":{"id":"doi:10.1109/isbi53787.2023.10230440","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/isbi53787.2023.10230440","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://purehost.bath.ac.uk/ws/files/301111744/QMRI_MRF_NLEI_Reconstruction_2023.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042796796","display_name":"Ketan Fatania","orcid":"https://orcid.org/0000-0002-0681-8036"},"institutions":[{"id":"https://openalex.org/I51601045","display_name":"University of Bath","ror":"https://ror.org/002h8g185","country_code":"GB","type":"education","lineage":["https://openalex.org/I51601045"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Ketan Fatania","raw_affiliation_strings":["University of Bath,Department of Computer Science,UK","Department of Computer Science, University of Bath, UK"],"affiliations":[{"raw_affiliation_string":"University of Bath,Department of Computer Science,UK","institution_ids":["https://openalex.org/I51601045"]},{"raw_affiliation_string":"Department of Computer Science, University of Bath, UK","institution_ids":["https://openalex.org/I51601045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063812664","display_name":"Kwai Y. Chau","orcid":null},"institutions":[{"id":"https://openalex.org/I51601045","display_name":"University of Bath","ror":"https://ror.org/002h8g185","country_code":"GB","type":"education","lineage":["https://openalex.org/I51601045"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kwai Y. Chau","raw_affiliation_strings":["University of Bath,Department of Computer Science,UK","Department of Computer Science, University of Bath, UK"],"affiliations":[{"raw_affiliation_string":"University of Bath,Department of Computer Science,UK","institution_ids":["https://openalex.org/I51601045"]},{"raw_affiliation_string":"Department of Computer Science, University of Bath, UK","institution_ids":["https://openalex.org/I51601045"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004509039","display_name":"Carolin M. Pirkl","orcid":"https://orcid.org/0000-0002-5759-5290"},"institutions":[{"id":"https://openalex.org/I189448455","display_name":"General Electric (Spain)","ror":"https://ror.org/04gbh9b75","country_code":"ES","type":"company","lineage":["https://openalex.org/I1332737386","https://openalex.org/I189448455"]},{"id":"https://openalex.org/I4210153902","display_name":"Siemens Healthcare (Germany)","ror":"https://ror.org/0449c4c15","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210153902"]}],"countries":["DE","ES"],"is_corresponding":false,"raw_author_name":"Carolin M. Pirkl","raw_affiliation_strings":["GE Healthcare,Germany","GE Healthcare, Germany"],"affiliations":[{"raw_affiliation_string":"GE Healthcare,Germany","institution_ids":["https://openalex.org/I189448455"]},{"raw_affiliation_string":"GE Healthcare, Germany","institution_ids":["https://openalex.org/I4210153902"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018118817","display_name":"Marion I. Menzel","orcid":"https://orcid.org/0000-0003-0087-9134"},"institutions":[{"id":"https://openalex.org/I4210106192","display_name":"Technische Hochschule Ingolstadt","ror":"https://ror.org/02bxzcy64","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210106192"]},{"id":"https://openalex.org/I189448455","display_name":"General Electric (Spain)","ror":"https://ror.org/04gbh9b75","country_code":"ES","type":"company","lineage":["https://openalex.org/I1332737386","https://openalex.org/I189448455"]},{"id":"https://openalex.org/I4210153902","display_name":"Siemens Healthcare (Germany)","ror":"https://ror.org/0449c4c15","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210153902"]},{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE","ES"],"is_corresponding":false,"raw_author_name":"Marion I. Menzel","raw_affiliation_strings":["GE Healthcare,Germany","Department of Physics, Technical University of Munich, Germany","GE Healthcare, Germany","AImotion Bavaria, Technische Hochschule Ingolstadt, Germany"],"affiliations":[{"raw_affiliation_string":"GE Healthcare,Germany","institution_ids":["https://openalex.org/I189448455"]},{"raw_affiliation_string":"Department of Physics, Technical University of Munich, Germany","institution_ids":["https://openalex.org/I62916508"]},{"raw_affiliation_string":"GE Healthcare, Germany","institution_ids":["https://openalex.org/I4210153902"]},{"raw_affiliation_string":"AImotion Bavaria, Technische Hochschule Ingolstadt, Germany","institution_ids":["https://openalex.org/I4210106192"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056404513","display_name":"Mohammad Golbabaee","orcid":"https://orcid.org/0000-0001-5822-2990"},"institutions":[{"id":"https://openalex.org/I51601045","display_name":"University of Bath","ror":"https://ror.org/002h8g185","country_code":"GB","type":"education","lineage":["https://openalex.org/I51601045"]},{"id":"https://openalex.org/I36234482","display_name":"University of Bristol","ror":"https://ror.org/0524sp257","country_code":"GB","type":"education","lineage":["https://openalex.org/I36234482"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mohammad Golbabaee","raw_affiliation_strings":["University of Bath,Department of Computer Science,UK","Department of Computer Science, University of Bath, UK","Department of Engineering Mathematics, University of Bristol, UK"],"affiliations":[{"raw_affiliation_string":"University of Bath,Department of Computer Science,UK","institution_ids":["https://openalex.org/I51601045"]},{"raw_affiliation_string":"Department of Computer Science, University of Bath, UK","institution_ids":["https://openalex.org/I51601045"]},{"raw_affiliation_string":"Department of Engineering Mathematics, University of Bristol, UK","institution_ids":["https://openalex.org/I36234482"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5042796796"],"corresponding_institution_ids":["https://openalex.org/I51601045"],"apc_list":null,"apc_paid":null,"fwci":0.6811,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.71879531,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8033111095428467},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.7003357410430908},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6997321248054504},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6081812381744385},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.6043003797531128},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5875245928764343},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5580172538757324},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5247205495834351},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5197941064834595},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4992716312408447},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.4617021679878235},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2813020646572113},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.07908234000205994},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06998124718666077}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8033111095428467},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7003357410430908},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6997321248054504},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6081812381744385},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6043003797531128},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5875245928764343},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5580172538757324},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5247205495834351},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5197941064834595},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4992716312408447},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.4617021679878235},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2813020646572113},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.07908234000205994},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06998124718666077},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/isbi53787.2023.10230440","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/isbi53787.2023.10230440","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},{"id":"pmh:oai:purehost.bath.ac.uk:openaire_cris_publications/656aea88-62fc-4b6d-b510-1be50e0e8d6b","is_oa":true,"landing_page_url":"https://researchportal.bath.ac.uk/en/publications/656aea88-62fc-4b6d-b510-1be50e0e8d6b","pdf_url":"https://purehost.bath.ac.uk/ws/files/301111744/QMRI_MRF_NLEI_Reconstruction_2023.pdf","source":{"id":"https://openalex.org/S4377196294","display_name":"Pure (University of Bath)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I51601045","host_organization_name":"University of Bath","host_organization_lineage":["https://openalex.org/I51601045"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fatania, K, Chau, K Y, Pirkl, C M, Menzel, M I & Golbabaee, M 2023, Nonlinear Equivariant Imaging : Learning Multi-Parametric Tissue Mapping without Ground Truth for Compressive Quantitative MRI. in 2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023. Proceedings - International Symposium on Biomedical Imaging, vol. 2023-April, IEEE, U. S. A., 20th IEEE International Symposium on Biomedical Imaging, ISBI 2023, Cartagena, Colombia, 18/04/23. https://doi.org/10.1109/ISBI53787.2023.10230440","raw_type":"contributionToPeriodical"},{"id":"pmh:oai:purehost.bath.ac.uk:openaire/656aea88-62fc-4b6d-b510-1be50e0e8d6b","is_oa":true,"landing_page_url":"https://researchportal.bath.ac.uk/files/301111744/QMRI_MRF_NLEI_Reconstruction_2023.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4377196294","display_name":"Pure (University of Bath)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I51601045","host_organization_name":"University of Bath","host_organization_lineage":["https://openalex.org/I51601045"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fatania, K, Chau, K Y, Pirkl, C M, Menzel, M I & Golbabaee, M 2023, Nonlinear Equivariant Imaging : Learning Multi-Parametric Tissue Mapping without Ground Truth for Compressive Quantitative MRI. in 2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023. Proceedings - International Symposium on Biomedical Imaging, vol. 2023-April, IEEE, U. S. A., 20th IEEE International Symposium on Biomedical Imaging, ISBI 2023, Cartagena, Colombia, 18/04/23. https://doi.org/10.1109/ISBI53787.2023.10230440","raw_type":"contributionToPeriodical"}],"best_oa_location":{"id":"pmh:oai:purehost.bath.ac.uk:openaire_cris_publications/656aea88-62fc-4b6d-b510-1be50e0e8d6b","is_oa":true,"landing_page_url":"https://researchportal.bath.ac.uk/en/publications/656aea88-62fc-4b6d-b510-1be50e0e8d6b","pdf_url":"https://purehost.bath.ac.uk/ws/files/301111744/QMRI_MRF_NLEI_Reconstruction_2023.pdf","source":{"id":"https://openalex.org/S4377196294","display_name":"Pure (University of Bath)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I51601045","host_organization_name":"University of Bath","host_organization_lineage":["https://openalex.org/I51601045"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fatania, K, Chau, K Y, Pirkl, C M, Menzel, M I & Golbabaee, M 2023, Nonlinear Equivariant Imaging : Learning Multi-Parametric Tissue Mapping without Ground Truth for Compressive Quantitative MRI. in 2023 IEEE International Symposium on Biomedical Imaging, ISBI 2023. Proceedings - International Symposium on Biomedical Imaging, vol. 2023-April, IEEE, U. S. A., 20th IEEE International Symposium on Biomedical Imaging, ISBI 2023, Cartagena, Colombia, 18/04/23. https://doi.org/10.1109/ISBI53787.2023.10230440","raw_type":"contributionToPeriodical"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8237994210","display_name":null,"funder_award_id":"EP/X001091/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G8514421286","display_name":"Deep compressive quantitative MRI imaging","funder_award_id":"EP/X001091/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386362590.pdf","grobid_xml":"https://content.openalex.org/works/W4386362590.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W1510815927","https://openalex.org/W1963427860","https://openalex.org/W2061708033","https://openalex.org/W2144288697","https://openalex.org/W2944556446","https://openalex.org/W2980111715","https://openalex.org/W3092052495","https://openalex.org/W3115858671","https://openalex.org/W4200630256","https://openalex.org/W4214521665","https://openalex.org/W4226344018","https://openalex.org/W4283311281"],"related_works":["https://openalex.org/W2580650124","https://openalex.org/W4386190339","https://openalex.org/W2968424575","https://openalex.org/W3142333283","https://openalex.org/W3122088529","https://openalex.org/W2082465502","https://openalex.org/W2896778670","https://openalex.org/W1928301487","https://openalex.org/W2151220638","https://openalex.org/W2725829804"],"abstract_inverted_index":{"Current":[0],"state-of-the-art":[1],"reconstruction":[2],"for":[3,39,50,53,77],"quantitative":[4],"tissue":[5,26,81],"maps":[6],"from":[7,90,108],"fast,":[8],"compressive,":[9],"Magnetic":[10],"Resonance":[11],"Fingerprinting":[12],"(MRF),":[13],"use":[14],"supervised":[15,135],"deep":[16,54],"learning,":[17],"with":[18],"the":[19,48,60,66,91,132],"drawback":[20],"of":[21,93,99,134],"requiring":[22],"high-fidelity":[23],"ground":[24,51],"truth":[25,52],"map":[27],"training":[28],"data":[29,95],"which":[30],"is":[31],"limited.":[32],"This":[33],"paper":[34],"proposes":[35],"NonLinear":[36],"Equivariant":[37,62],"Imaging":[38,63],"MRF":[40,55,67,73,94],"(NLEIMRF),":[41],"a":[42,97,109,116],"self-supervised":[43],"learning":[44],"approach":[45],"to":[46,65,96],"eliminate":[47],"need":[49],"image":[56,101],"reconstruction.":[57],"NLEI-MRF":[58,79,129],"extends":[59],"recent":[61],"framework":[64],"nonlinear":[68,110],"inverse":[69],"problem.":[70],"Only":[71],"compressed-sampled":[72],"scans":[74],"are":[75,88,106],"used":[76],"training.":[78],"learns":[80],"mapping":[82],"using":[83],"spatiotemporal":[84],"priors:":[85],"spatial":[86],"priors":[87,105],"obtained":[89,107],"invariance":[92],"group":[98],"geometric":[100],"transformations,":[102],"while":[103],"temporal":[104],"Bloch":[111],"response":[112],"model":[113],"approximated":[114],"by":[115],"pre-trained":[117],"neural":[118],"network.":[119],"Tested":[120],"retrospectively":[121],"on":[122],"two":[123],"acquisition":[124],"settings,":[125],"we":[126],"observe":[127],"that":[128],"closely":[130],"approaches":[131],"performance":[133],"learning.":[136]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
