{"id":"https://openalex.org/W4394804911","doi":"https://doi.org/10.1109/tci.2024.3388869","title":"PINQI: An End-to-End Physics-Informed Approach to Learned Quantitative MRI Reconstruction","display_name":"PINQI: An End-to-End Physics-Informed Approach to Learned Quantitative MRI Reconstruction","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4394804911","doi":"https://doi.org/10.1109/tci.2024.3388869"},"language":"en","primary_location":{"id":"doi:10.1109/tci.2024.3388869","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tci.2024.3388869","pdf_url":"https://ieeexplore.ieee.org/ielx7/6745852/6960042/10499888.pdf","source":{"id":"https://openalex.org/S4210233665","display_name":"IEEE Transactions on Computational Imaging","issn_l":"2333-9403","issn":["2333-9403","2573-0436"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/6745852/6960042/10499888.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012190939","display_name":"Felix Zimmermann","orcid":"https://orcid.org/0000-0002-0862-8973"},"institutions":[{"id":"https://openalex.org/I1285933455","display_name":"Physikalisch-Technische Bundesanstalt","ror":"https://ror.org/05r3f7h03","country_code":"DE","type":"government","lineage":["https://openalex.org/I1285933455","https://openalex.org/I4210136623"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Felix F. Zimmermann","raw_affiliation_strings":["Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Berlin, Germany"],"raw_orcid":"https://orcid.org/0000-0002-0862-8973","affiliations":[{"raw_affiliation_string":"Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I1285933455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046209820","display_name":"Christoph Kolbitsch","orcid":"https://orcid.org/0000-0002-4355-8368"},"institutions":[{"id":"https://openalex.org/I1285933455","display_name":"Physikalisch-Technische Bundesanstalt","ror":"https://ror.org/05r3f7h03","country_code":"DE","type":"government","lineage":["https://openalex.org/I1285933455","https://openalex.org/I4210136623"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christoph Kolbitsch","raw_affiliation_strings":["Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Berlin, Germany"],"raw_orcid":"https://orcid.org/0000-0002-4355-8368","affiliations":[{"raw_affiliation_string":"Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I1285933455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058207847","display_name":"Patrick Schuenke","orcid":"https://orcid.org/0000-0002-3179-4830"},"institutions":[{"id":"https://openalex.org/I1285933455","display_name":"Physikalisch-Technische Bundesanstalt","ror":"https://ror.org/05r3f7h03","country_code":"DE","type":"government","lineage":["https://openalex.org/I1285933455","https://openalex.org/I4210136623"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Patrick Schuenke","raw_affiliation_strings":["Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Berlin, Germany"],"raw_orcid":"https://orcid.org/0000-0002-3179-4830","affiliations":[{"raw_affiliation_string":"Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I1285933455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010913753","display_name":"Andreas Kofler","orcid":"https://orcid.org/0000-0001-9169-2572"},"institutions":[{"id":"https://openalex.org/I1285933455","display_name":"Physikalisch-Technische Bundesanstalt","ror":"https://ror.org/05r3f7h03","country_code":"DE","type":"government","lineage":["https://openalex.org/I1285933455","https://openalex.org/I4210136623"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Andreas Kofler","raw_affiliation_strings":["Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Berlin, Germany"],"raw_orcid":"https://orcid.org/0000-0001-9169-2572","affiliations":[{"raw_affiliation_string":"Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I1285933455"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5012190939"],"corresponding_institution_ids":["https://openalex.org/I1285933455"],"apc_list":null,"apc_paid":null,"fwci":4.9696,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.95502425,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"10","issue":null,"first_page":"628","last_page":"639"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9987000226974487,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6313865780830383},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6137376427650452},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5901772975921631},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5824400186538696},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.5602023601531982},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5443938374519348},{"id":"https://openalex.org/keywords/data-acquisition","display_name":"Data acquisition","score":0.47858595848083496},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4749303460121155},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43686485290527344},{"id":"https://openalex.org/keywords/imaging-phantom","display_name":"Imaging phantom","score":0.4173153042793274},{"id":"https://openalex.org/keywords/differentiable-function","display_name":"Differentiable function","score":0.4100120961666107},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1749771237373352}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6313865780830383},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6137376427650452},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5901772975921631},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5824400186538696},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.5602023601531982},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5443938374519348},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.47858595848083496},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4749303460121155},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43686485290527344},{"id":"https://openalex.org/C104293457","wikidata":"https://www.wikidata.org/wiki/Q28324852","display_name":"Imaging phantom","level":2,"score":0.4173153042793274},{"id":"https://openalex.org/C202615002","wikidata":"https://www.wikidata.org/wiki/Q783507","display_name":"Differentiable function","level":2,"score":0.4100120961666107},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1749771237373352},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tci.2024.3388869","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tci.2024.3388869","pdf_url":"https://ieeexplore.ieee.org/ielx7/6745852/6960042/10499888.pdf","source":{"id":"https://openalex.org/S4210233665","display_name":"IEEE Transactions on Computational Imaging","issn_l":"2333-9403","issn":["2333-9403","2573-0436"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Imaging","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/tci.2024.3388869","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tci.2024.3388869","pdf_url":"https://ieeexplore.ieee.org/ielx7/6745852/6960042/10499888.pdf","source":{"id":"https://openalex.org/S4210233665","display_name":"IEEE Transactions on Computational Imaging","issn_l":"2333-9403","issn":["2333-9403","2573-0436"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Imaging","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5169014453","display_name":null,"funder_award_id":"372486779","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320319124","display_name":"European Partnership on Metrology","ror":null},{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4394804911.pdf","grobid_xml":"https://content.openalex.org/works/W4394804911.grobid-xml"},"referenced_works_count":66,"referenced_works":["https://openalex.org/W1534064374","https://openalex.org/W1544724604","https://openalex.org/W1594587862","https://openalex.org/W1901129140","https://openalex.org/W2029816571","https://openalex.org/W2051434435","https://openalex.org/W2055285572","https://openalex.org/W2075358160","https://openalex.org/W2100705753","https://openalex.org/W2117649283","https://openalex.org/W2124348301","https://openalex.org/W2133665775","https://openalex.org/W2134495751","https://openalex.org/W2144288697","https://openalex.org/W2145020729","https://openalex.org/W2149392970","https://openalex.org/W2318835073","https://openalex.org/W2415524820","https://openalex.org/W2505728881","https://openalex.org/W2507707535","https://openalex.org/W2594014149","https://openalex.org/W2626325717","https://openalex.org/W2760103357","https://openalex.org/W2773850766","https://openalex.org/W2798456213","https://openalex.org/W2890798034","https://openalex.org/W2891118307","https://openalex.org/W2904816510","https://openalex.org/W2962734274","https://openalex.org/W2963820951","https://openalex.org/W2963855133","https://openalex.org/W3026690960","https://openalex.org/W3034546843","https://openalex.org/W3092530614","https://openalex.org/W3100730608","https://openalex.org/W3127154058","https://openalex.org/W3133487499","https://openalex.org/W3133689921","https://openalex.org/W3172058019","https://openalex.org/W3179592584","https://openalex.org/W4205753121","https://openalex.org/W4220796273","https://openalex.org/W4225015076","https://openalex.org/W4235806146","https://openalex.org/W4236316114","https://openalex.org/W4238100585","https://openalex.org/W4249760698","https://openalex.org/W4296962111","https://openalex.org/W4306178244","https://openalex.org/W4312282303","https://openalex.org/W4313524971","https://openalex.org/W4383484266","https://openalex.org/W4391452853","https://openalex.org/W6631190155","https://openalex.org/W6635560335","https://openalex.org/W6678738811","https://openalex.org/W6693919493","https://openalex.org/W6725192724","https://openalex.org/W6729455701","https://openalex.org/W6734122017","https://openalex.org/W6738279954","https://openalex.org/W6757817989","https://openalex.org/W6767977373","https://openalex.org/W6774776664","https://openalex.org/W6846023738","https://openalex.org/W6870843996"],"related_works":["https://openalex.org/W1965977581","https://openalex.org/W2061980133","https://openalex.org/W2050855072","https://openalex.org/W2077506191","https://openalex.org/W2387685679","https://openalex.org/W3134728064","https://openalex.org/W2115238236","https://openalex.org/W2374214022","https://openalex.org/W2347781941","https://openalex.org/W4298004047"],"abstract_inverted_index":{"Quantitative":[0],"Magnetic":[1],"Resonance":[2],"Imaging":[3],"(qMRI)":[4],"enables":[5,135],"the":[6,26,44,52,56,61,65,81,84,126,139,143,151,165,201,212],"reproducible":[7],"measurement":[8],"of":[9,125,141,153,167,203,214],"biophysical":[10],"parameters":[11],"in":[12,17,164,217],"tissue.":[13],"The":[14,198],"challenge":[15],"lies":[16],"solving":[18],"a":[19,74,92,177,189],"nonlinear,":[20],"ill-posed":[21],"inverse":[22],"problem":[23],"to":[24,49,110,137],"obtain":[25],"desired":[27],"tissue":[28],"parameter":[29,131],"maps":[30],"from":[31,188,195],"acquired":[32,187],"raw":[33],"data.":[34],"While":[35],"various":[36],"learned":[37,46,89,147],"and":[38,64,88,114,130,146,192,210],"non-learned":[39],"approaches":[40,163],"have":[41],"been":[42],"proposed,":[43],"existing":[45,208],"methods":[47,209],"fail":[48],"fully":[50],"exploit":[51],"prior":[53],"knowledge":[54,82],"about":[55,83],"underlying":[57],"MR":[58],"physics,":[59],"i.e.":[60],"signal":[62,144],"model":[63,145],"acquisition":[66,86],"model.":[67],"In":[68],"this":[69],"paper,":[70],"we":[71],"propose":[72],"PINQI,":[73],"novel":[75],"qMRI":[76],"reconstruction":[77],"method":[78,216],"that":[79],"integrates":[80],"signal,":[85],"model,":[87],"regularization":[90,124],"into":[91],"single":[93],"end-to-end":[94],"trainable":[95],"neural":[96],"network.":[97],"Our":[98],"approach":[99],"is":[100],"based":[101],"on":[102],"unrolled":[103],"alternating":[104],"optimization,":[105],"utilizing":[106],"differentiable":[107],"optimization":[108,116],"blocks":[109],"solve":[111],"inner":[112],"linear":[113],"non-linear":[115],"tasks,":[117],"as":[118,120,181,183],"well":[119,182],"convolutional":[121],"layers":[122],"for":[123],"intermediate":[127],"qualitative":[128],"images":[129],"maps.":[132],"This":[133],"design":[134],"PINQI":[136],"leverage":[138],"advantages":[140],"both":[142,176],"regularization.":[148],"We":[149],"evaluate":[150],"performance":[152],"our":[154,204,215],"proposed":[155,205],"network":[156],"by":[157],"comparing":[158],"it":[159],"with":[160],"recently":[161],"published":[162],"context":[166],"highly":[168],"undersampled":[169],"<inline-formula":[170],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[171],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[172],"notation=\"LaTeX\">$T_{1}$</tex-math></inline-formula>":[173],"-mapping,":[174],"using":[175],"simulated":[178],"brain":[179],"dataset,":[180],"real":[184],"scanner":[185],"data":[186,194],"physical":[190],"phantom":[191],"in-vivo":[193],"healthy":[196],"volunteers.":[197],"results":[199],"demonstrate":[200],"superiority":[202],"solution":[206],"over":[207],"highlight":[211],"effectiveness":[213],"real-world":[218],"scenarios.":[219]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-28T14:05:53.105641","created_date":"2025-10-10T00:00:00"}