{"id":"https://openalex.org/W2805482402","doi":"https://doi.org/10.1109/isbi.2018.8363663","title":"Model based image reconstruction using deep learned priors (MODL)","display_name":"Model based image reconstruction using deep learned priors (MODL)","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2805482402","doi":"https://doi.org/10.1109/isbi.2018.8363663","mag":"2805482402","pmid":"https://pubmed.ncbi.nlm.nih.gov/33584973","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/7876898"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2018.8363663","doi":"https://doi.org/10.1109/isbi.2018.8363663","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363663","pdf_url":null,"source":{"id":"https://openalex.org/S4363605129","display_name":"IEEE International Symposium on Biomedical Imaging (ISBI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7876898","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076929884","display_name":"Hemant Kumar Aggarwal","orcid":"https://orcid.org/0000-0002-3756-9765","observed_orcids":["https://orcid.org/0000-0002-3756-9765"]},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hemant Kumar Aggarwal","raw_affiliation_strings":["University of Iowa, Iowa, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Iowa, Iowa, USA","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035948800","display_name":"Merry Mani","orcid":"https://orcid.org/0000-0001-8602-1109","observed_orcids":["https://orcid.org/0000-0001-8602-1109"]},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Merry P. Mani","raw_affiliation_strings":["University of Iowa, Iowa, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Iowa, Iowa, USA","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072299998","display_name":"Mathews Jacob","orcid":"https://orcid.org/0000-0001-6196-3933","observed_orcids":["https://orcid.org/0000-0001-6196-3933"]},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mathews Jacob","raw_affiliation_strings":["University of Iowa, Iowa, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Iowa, Iowa, USA","institution_ids":["https://openalex.org/I126307644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I126307644"],"apc_list":null,"apc_paid":null,"fwci":4.754,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.95423239,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"2018","issue":null,"first_page":"671","last_page":"674"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.7997999787330627,"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":0.7997999787330627,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.15539999306201935,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.013299999758601189,"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/model-based-image-reconstruction","display_name":"model-based image reconstruction","score":0.9710000157356262},{"id":"https://openalex.org/keywords/alternating-direction-method-of-multipliers","display_name":"alternating direction method of multipliers","score":0.5879999995231628},{"id":"https://openalex.org/keywords/unrolling","display_name":"unrolling","score":0.5320000052452087},{"id":"https://openalex.org/keywords/data-consistency","display_name":"data consistency","score":0.6159999966621399},{"id":"https://openalex.org/keywords/image-denoising","display_name":"image denoising","score":0.7710000276565552},{"id":"https://openalex.org/keywords/forward-model","display_name":"forward model","score":0.6000000238418579}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7507633566856384},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6533735990524292},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5840485095977783},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5502007603645325},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5381298065185547},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5301663875579834},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.5232393145561218},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5080437660217285},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.464459627866745},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.45121055841445923},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41989439725875854},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.414673388004303},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40581226348876953},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.08815193176269531}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/isbi.2018.8363663","doi":"https://doi.org/10.1109/isbi.2018.8363663","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2018.8363663","pdf_url":null,"source":{"id":"https://openalex.org/S4363605129","display_name":"IEEE International Symposium on Biomedical Imaging (ISBI)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)","raw_type":"proceedings-article"},{"id":"pmid:33584973","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33584973","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. IEEE International Symposium on Biomedical Imaging","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:7876898","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7876898","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Proc IEEE Int Symp Biomed Imaging","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:7876898","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7876898","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Proc IEEE Int Symp Biomed Imaging","raw_type":"Text"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G9000874707","display_name":"Novel Computational Framework for Free-Breathing & Ungated Dynamic MRI","funder_award_id":"R01EB019961","funder_id":"https://openalex.org/F4320337363","funder_display_name":"National Institute of Biomedical Imaging and Bioengineering"}],"funders":[{"id":"https://openalex.org/F4320337363","display_name":"National Institute of Biomedical Imaging and Bioengineering","ror":"https://ror.org/00372qc85"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2090457307","https://openalex.org/W2101161912","https://openalex.org/W2108067537","https://openalex.org/W2156739854","https://openalex.org/W2167396304","https://openalex.org/W2346305596","https://openalex.org/W2574952845","https://openalex.org/W2604388535","https://openalex.org/W2620324432","https://openalex.org/W2631883531","https://openalex.org/W2950936580"],"related_works":["https://openalex.org/W2906587342","https://openalex.org/W2773850766","https://openalex.org/W3172319064","https://openalex.org/W2922528425","https://openalex.org/W4386559571","https://openalex.org/W3030204642","https://openalex.org/W3019797898","https://openalex.org/W4317479422","https://openalex.org/W2972087504","https://openalex.org/W3189982288"],"abstract_inverted_index":{"We":[0,19],"introduce":[1],"a":[2,10,22,28,43,99],"model-based":[3,76],"image":[4],"reconstruction":[5,128],"framework,":[6],"where":[7],"we":[8],"use":[9,59,97,121],"deep":[11,44],"convolution":[12],"neural":[13],"network":[14,45,108],"(CNN)":[15],"based":[16,30],"regularization":[17],"prior.":[18],"rely":[20],"on":[21],"recursive":[23,40],"algorithm,":[24],"which":[25,68,87],"alternates":[26],"between":[27],"CNN":[29,63],"denoising":[31],"step":[32],"and":[33,109],"enforcement":[34],"of":[35,54,60,84,92,98,106,122],"data":[36,94],"consistency.":[37],"Unrolling":[38],"the":[39,58,61,70,75,82,90,104,107,111,123],"algorithm":[41],"yields":[42],"that":[46],"is":[47,57],"trained":[48],"using":[49],"backpropagation.":[50],"The":[51,96,120],"unique":[52],"aspect":[53],"this":[55,79],"method":[56],"same":[62],"weights":[64],"at":[65],"each":[66],"iteration,":[67],"makes":[69],"resulting":[71],"structure":[72],"consistent":[73],"with":[74],"formulation.":[77],"Also,":[78],"approach":[80],"reduces":[81,103],"number":[83],"trainable":[85],"parameters,":[86],"hence":[88],"lower":[89],"amount":[91],"training":[93],"needed.":[95],"forward":[100],"model":[101],"also":[102],"size":[105],"enables":[110],"exploitation":[112],"additional":[113],"prior":[114],"information":[115],"available":[116],"from":[117],"calibration":[118],"data.":[119],"framework":[124],"for":[125],"multichannel":[126],"MRI":[127],"provides":[129],"improved":[130],"reconstructions,":[131],"compared":[132],"to":[133],"other":[134],"state-of-the-art":[135],"methods.":[136]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":4}],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2018-06-13T00:00:00"}
