{"id":"https://openalex.org/W4406961538","doi":"https://doi.org/10.1109/isbi60581.2025.10981200","title":"Three-Dimensional Diffusion-Weighted Multi-Slab MRI with Slice Profile Compensation Using Deep Energy Model","display_name":"Three-Dimensional Diffusion-Weighted Multi-Slab MRI with Slice Profile Compensation Using Deep Energy Model","publication_year":2025,"publication_date":"2025-04-14","ids":{"openalex":"https://openalex.org/W4406961538","doi":"https://doi.org/10.1109/isbi60581.2025.10981200","pmid":"https://pubmed.ncbi.nlm.nih.gov/39975424"},"language":"en","primary_location":{"id":"doi:10.1109/isbi60581.2025.10981200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi60581.2025.10981200","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2501.17152","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067151510","display_name":"Reza Ghorbani","orcid":"https://orcid.org/0000-0001-8997-1273"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Reza Ghorbani","raw_affiliation_strings":["University of Virginia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Virginia","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072491757","display_name":"Jyothi Rikhab Chand","orcid":"https://orcid.org/0000-0002-8335-6103"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jyothi Rikhab Chand","raw_affiliation_strings":["University of Virginia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Virginia","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039720212","display_name":"Chu\u2010Yu Lee","orcid":"https://orcid.org/0000-0001-5288-3309"},"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":"Chu-Yu Lee","raw_affiliation_strings":["University of Iowa"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Iowa","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072299998","display_name":"Mathews Jacob","orcid":"https://orcid.org/0000-0001-6196-3933"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mathews Jacob","raw_affiliation_strings":["University of Virginia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Virginia","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035948800","display_name":"Merry Mani","orcid":"https://orcid.org/0000-0001-8602-1109"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Merry Mani","raw_affiliation_strings":["University of Virginia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Virginia","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.9998999834060669,"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.9998999834060669,"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/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9940999746322632,"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/T11885","display_name":"MRI in cancer diagnosis","score":0.9934999942779541,"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/slab","display_name":"Slab","score":0.8059054613113403},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6814206838607788},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6041573882102966},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.5677730441093445},{"id":"https://openalex.org/keywords/aliasing","display_name":"Aliasing","score":0.5236555933952332},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5179283022880554},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48663076758384705},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.4638431668281555},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4603744149208069},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.43481796979904175},{"id":"https://openalex.org/keywords/diffusion-imaging","display_name":"Diffusion imaging","score":0.41708970069885254},{"id":"https://openalex.org/keywords/diffusion-mri","display_name":"Diffusion MRI","score":0.4151986837387085},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3629363775253296},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23805269598960876},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.21681126952171326},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.176486074924469}],"concepts":[{"id":"https://openalex.org/C113740112","wikidata":"https://www.wikidata.org/wiki/Q5904738","display_name":"Slab","level":2,"score":0.8059054613113403},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6814206838607788},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6041573882102966},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.5677730441093445},{"id":"https://openalex.org/C4069607","wikidata":"https://www.wikidata.org/wiki/Q868732","display_name":"Aliasing","level":3,"score":0.5236555933952332},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5179283022880554},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48663076758384705},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.4638431668281555},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4603744149208069},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.43481796979904175},{"id":"https://openalex.org/C2992283565","wikidata":"https://www.wikidata.org/wiki/Q899360","display_name":"Diffusion imaging","level":4,"score":0.41708970069885254},{"id":"https://openalex.org/C149550507","wikidata":"https://www.wikidata.org/wiki/Q899360","display_name":"Diffusion MRI","level":3,"score":0.4151986837387085},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3629363775253296},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23805269598960876},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.21681126952171326},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.176486074924469},{"id":"https://openalex.org/C8058405","wikidata":"https://www.wikidata.org/wiki/Q46255","display_name":"Geophysics","level":1,"score":0.0},{"id":"https://openalex.org/C136536468","wikidata":"https://www.wikidata.org/wiki/Q1225894","display_name":"Undersampling","level":2,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/isbi60581.2025.10981200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi60581.2025.10981200","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},{"id":"pmid:39975424","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39975424","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,"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":"ArXiv","raw_type":null},{"id":"pmh:oai:arXiv.org:2501.17152","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2501.17152","pdf_url":"https://arxiv.org/pdf/2501.17152","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:pubmedcentral.nih.gov:11838706","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11838706","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,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ArXiv","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2501.17152","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2501.17152","pdf_url":"https://arxiv.org/pdf/2501.17152","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","score":0.9100000262260437,"display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G5256840680","display_name":null,"funder_award_id":"R01EB031169,R01EB031169-02S1,R01-AG067078,R01-EB019961","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4406961538.pdf"},"referenced_works_count":7,"referenced_works":["https://openalex.org/W1504742461","https://openalex.org/W1539131666","https://openalex.org/W2013035813","https://openalex.org/W2151354228","https://openalex.org/W2963814976","https://openalex.org/W3167568784","https://openalex.org/W4401806460"],"related_works":["https://openalex.org/W2139021045","https://openalex.org/W2292818317","https://openalex.org/W1855712746","https://openalex.org/W4394712012","https://openalex.org/W2007889670","https://openalex.org/W6468075","https://openalex.org/W4233198143","https://openalex.org/W2112709210","https://openalex.org/W2100699146","https://openalex.org/W3100376342"],"abstract_inverted_index":{"Three-dimensional":[0],"(3D)":[1],"multi-slab":[2],"acquisition":[3],"is":[4,26,50],"a":[5,73,81,120],"technique":[6,25],"frequently":[7],"employed":[8],"in":[9,13],"high-resolution":[10,59,127],"diffusion-weighted":[11],"MRI":[12,55],"order":[14],"to":[15,90,109],"achieve":[16],"the":[17,42,93,101],"best":[18],"signal-to-noise":[19],"ratio":[20],"(SNR)":[21],"efficiency.":[22],"However,":[23],"this":[24,48,69],"limited":[27],"by":[28],"slab":[29,75,94],"boundary":[30],"artifacts":[31],"that":[32,100],"cause":[33],"intensity":[34],"fluctuations":[35],"and":[36,57,65,111,123],"aliasing":[37],"between":[38],"slabs":[39],"which":[40],"reduces":[41],"accuracy":[43],"of":[44],"anatomical":[45,136],"imaging.":[46],"Addressing":[47],"issue":[49],"crucial":[51],"for":[52,63,126],"advancing":[53],"diffusion":[54,129],"quality":[56,107],"making":[58],"imaging":[60,137],"more":[61,121,134],"feasible":[62],"clinical":[64],"research":[66],"applications.":[67,140],"In":[68],"work,":[70],"we":[71],"propose":[72],"regularized":[74,116],"profile":[76],"encoding":[77],"(PEN)":[78],"method":[79,103],"within":[80],"Plug-and-Play":[82],"ADMM":[83],"framework,":[84],"incorporating":[85],"multi-scale":[86],"energy":[87],"(MuSE)":[88],"regularization":[89],"effectively":[91],"improve":[92],"combined":[95],"reconstruction.":[96],"Experimental":[97],"results":[98],"demonstrate":[99],"proposed":[102],"significantly":[104],"improves":[105],"image":[106],"compared":[108],"non-regularized":[110],"TV-regularized":[112],"PEN":[113,117],"approaches.":[114],"The":[115],"framework":[118],"provides":[119],"robust":[122],"efficient":[124],"solution":[125],"3D":[128],"MRI,":[130],"potentially":[131],"enabling":[132],"clearer,":[133],"reliable":[135],"across":[138],"various":[139]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
