{"id":"https://openalex.org/W7166726252","doi":"https://doi.org/10.1016/j.neuroimage.2026.122092","title":"Arterial spin labeling MRI denoising via locally adaptive regularization with structure-guided collaborative data selection","display_name":"Arterial spin labeling MRI denoising via locally adaptive regularization with structure-guided collaborative data selection","publication_year":2026,"publication_date":"2026-06-30","ids":{"openalex":"https://openalex.org/W7166726252","doi":"https://doi.org/10.1016/j.neuroimage.2026.122092","pmid":"https://pubmed.ncbi.nlm.nih.gov/42379401"},"language":"en","primary_location":{"id":"doi:10.1016/j.neuroimage.2026.122092","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.neuroimage.2026.122092","pdf_url":null,"source":{"id":"https://openalex.org/S103225281","display_name":"NeuroImage","issn_l":"1053-8119","issn":["1053-8119","1095-9572"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"NeuroImage","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1016/j.neuroimage.2026.122092","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079154623","display_name":"Hangfan Liu","orcid":"https://orcid.org/0000-0002-1207-7713"},"institutions":[{"id":"https://openalex.org/I126744593","display_name":"University of Maryland, Baltimore","ror":"https://ror.org/04rq5mt64","country_code":"US","type":"education","lineage":["https://openalex.org/I126744593"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hangfan Liu","raw_affiliation_strings":["Center for Advanced Imaging Research, University of Maryland School of Medicine, Baltimore, MD, 21202, USA. Electronic address: hangfan.liu@som.umaryland.edu"],"raw_orcid":"https://orcid.org/0000-0002-1207-7713","affiliations":[{"raw_affiliation_string":"Center for Advanced Imaging Research, University of Maryland School of Medicine, Baltimore, MD, 21202, USA. Electronic address: hangfan.liu@som.umaryland.edu","institution_ids":["https://openalex.org/I126744593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073882193","display_name":"BJ Li","orcid":null},"institutions":[{"id":"https://openalex.org/I126744593","display_name":"University of Maryland, Baltimore","ror":"https://ror.org/04rq5mt64","country_code":"US","type":"education","lineage":["https://openalex.org/I126744593"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bo Li","raw_affiliation_strings":["Center for Advanced Imaging Research, University of Maryland School of Medicine, Baltimore, MD, 21202, USA. Electronic address: boli3@mgh.harvard.edu"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Advanced Imaging Research, University of Maryland School of Medicine, Baltimore, MD, 21202, USA. Electronic address: boli3@mgh.harvard.edu","institution_ids":["https://openalex.org/I126744593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139680424","display_name":"John A Detre","orcid":null},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John A Detre","raw_affiliation_strings":["Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA. Electronic address: detre@pennmedicine.upenn.edu"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA. Electronic address: detre@pennmedicine.upenn.edu","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5139674419","display_name":"Ze Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I126744593","display_name":"University of Maryland, Baltimore","ror":"https://ror.org/04rq5mt64","country_code":"US","type":"education","lineage":["https://openalex.org/I126744593"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ze Wang","raw_affiliation_strings":["Center for Advanced Imaging Research, University of Maryland School of Medicine, Baltimore, MD, 21202, USA. Electronic address: ze.wang@som.umaryland.edu"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Advanced Imaging Research, University of Maryland School of Medicine, Baltimore, MD, 21202, USA. Electronic address: ze.wang@som.umaryland.edu","institution_ids":["https://openalex.org/I126744593"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5139674419"],"corresponding_institution_ids":["https://openalex.org/I126744593"],"apc_list":{"value":3450,"currency":"USD","value_usd":3450},"apc_paid":{"value":3450,"currency":"USD","value_usd":3450},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.76716196,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"338","issue":null,"first_page":"122092","last_page":"122092"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.7307999730110168,"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":0.7307999730110168,"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/T12381","display_name":"Electron Spin Resonance Studies","score":0.05570000037550926,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12603","display_name":"NMR spectroscopy and applications","score":0.0348999984562397,"subfield":{"id":"https://openalex.org/subfields/3106","display_name":"Nuclear and High Energy Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.7870000004768372},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.6690000295639038},{"id":"https://openalex.org/keywords/arterial-spin-labeling","display_name":"Arterial spin labeling","score":0.5777999758720398},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5410000085830688},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4578999876976013},{"id":"https://openalex.org/keywords/noisy-data","display_name":"Noisy data","score":0.3352999985218048},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.33219999074935913}],"concepts":[{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.7870000004768372},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6690000295639038},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6389999985694885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6186000108718872},{"id":"https://openalex.org/C3018723549","wikidata":"https://www.wikidata.org/wiki/Q56284158","display_name":"Arterial spin labeling","level":3,"score":0.5777999758720398},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5410000085830688},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4578999876976013},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.3352999985218048},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.33219999074935913},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3188999891281128},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.3172999918460846},{"id":"https://openalex.org/C2983327147","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Image denoising","level":3,"score":0.30979999899864197},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3091999888420105},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.30399999022483826},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.3012999892234802},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.28600001335144043},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C177462420","wikidata":"https://www.wikidata.org/wiki/Q7531731","display_name":"Site-directed spin labeling","level":3,"score":0.26249998807907104},{"id":"https://openalex.org/C153914771","wikidata":"https://www.wikidata.org/wiki/Q5227343","display_name":"Data reduction","level":2,"score":0.2572999894618988}],"mesh":[{"descriptor_ui":"D000098642","descriptor_name":"Perfusion Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000098","qualifier_name":"blood supply","is_major_topic":true},{"descriptor_ui":"D002560","descriptor_name":"Cerebrovascular Circulation","qualifier_ui":"Q000502","qualifier_name":"physiology","is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D013113","descriptor_name":"Spin Labels","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D059629","descriptor_name":"Signal-To-Noise Ratio","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1016/j.neuroimage.2026.122092","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.neuroimage.2026.122092","pdf_url":null,"source":{"id":"https://openalex.org/S103225281","display_name":"NeuroImage","issn_l":"1053-8119","issn":["1053-8119","1095-9572"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"NeuroImage","raw_type":"journal-article"},{"id":"pmid:42379401","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42379401","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":"NeuroImage","raw_type":"Journal Article"}],"best_oa_location":{"id":"doi:10.1016/j.neuroimage.2026.122092","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.neuroimage.2026.122092","pdf_url":null,"source":{"id":"https://openalex.org/S103225281","display_name":"NeuroImage","issn_l":"1053-8119","issn":["1053-8119","1095-9572"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"NeuroImage","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306080","display_name":"Foundation for the National Institutes of Health","ror":"https://ror.org/00k86s890"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W240388180","https://openalex.org/W1466544342","https://openalex.org/W1841182567","https://openalex.org/W1939737569","https://openalex.org/W1971057552","https://openalex.org/W1973364640","https://openalex.org/W1982471090","https://openalex.org/W1989854445","https://openalex.org/W1997555772","https://openalex.org/W2005305968","https://openalex.org/W2007543006","https://openalex.org/W2007734075","https://openalex.org/W2009828262","https://openalex.org/W2010568455","https://openalex.org/W2012056804","https://openalex.org/W2017862826","https://openalex.org/W2056361646","https://openalex.org/W2056370875","https://openalex.org/W2083138589","https://openalex.org/W2103033985","https://openalex.org/W2116641010","https://openalex.org/W2124234909","https://openalex.org/W2127870457","https://openalex.org/W2130010412","https://openalex.org/W2131867635","https://openalex.org/W2133665775","https://openalex.org/W2146456738","https://openalex.org/W2161167354","https://openalex.org/W2169348819","https://openalex.org/W2177917702","https://openalex.org/W2338117771","https://openalex.org/W2547222931","https://openalex.org/W2620199441","https://openalex.org/W2737580057","https://openalex.org/W2746670893","https://openalex.org/W2766508988","https://openalex.org/W2770470956","https://openalex.org/W2901239122","https://openalex.org/W2904016341","https://openalex.org/W2962769133","https://openalex.org/W3000078575","https://openalex.org/W3005694318","https://openalex.org/W3158609413","https://openalex.org/W3185385692","https://openalex.org/W3210987080","https://openalex.org/W4233867216","https://openalex.org/W4292296635","https://openalex.org/W4304479347","https://openalex.org/W4317781105","https://openalex.org/W4389464979","https://openalex.org/W7117123875"],"related_works":[],"abstract_inverted_index":{"Arterial":[0],"spin":[1,30,35],"labeled":[2,31],"(ASL)":[3],"perfusion":[4,214],"MRI":[5,22,48,205,243],"is":[6,23,57,63,68],"the":[7,26,29,34,41,60,95,99,113,148,154,158,163,171,179,210,225],"only":[8],"non-invasive":[9],"and":[10,33,66,102,135],"non-radioactive":[11],"technique":[12],"for":[13,241],"measuring":[14],"regional":[15],"tissue":[16],"perfusion.":[17],"Perfusion":[18],"signal":[19],"in":[20,178],"ASL":[21,47,204,213,242],"derived":[24],"from":[25],"difference":[27],"between":[28,98],"image":[32],"untagged":[36],"control":[37,103],"image.":[38],"Limited":[39],"by":[40],"T1":[42],"decay":[43],"of":[44,150,157,162,212,220],"arterial":[45],"blood,":[46],"has":[49],"an":[50,82],"intrinsic":[51],"low":[52],"signal-to-noise-ratio.":[53],"Solving":[54],"this":[55,78],"problem":[56],"challenging":[58],"because":[59],"ground":[61],"truth":[62],"often":[64],"unknown,":[65],"it":[67],"difficult":[69],"to":[70,106,111,120,127],"preserve":[71],"textures":[72],"when":[73],"suppressing":[74],"heavy":[75],"noise.":[76],"In":[77],"paper":[79],"we":[80,146],"propose":[81],"unsupervised":[83],"Locally":[84],"Adaptive":[85],"regularization":[86,118],"with":[87,131,141,224],"Collaborative":[88],"data":[89],"Selection":[90],"(LACS)":[91],"scheme,":[92],"which":[93],"exploits":[94,175],"high":[96],"affinity":[97],"paired":[100],"label":[101],"(L/C)":[104],"images":[105],"select":[107],"highly":[108],"correlated":[109],"contents":[110],"form":[112],"low-rank":[114,117,159],"matrices.":[115],"The":[116,233],"applied":[119],"such":[121],"matrices":[122,152],"could":[123,236],"be":[124],"better":[125],"adapted":[126],"local":[128,143],"structures":[129],"compared":[130,140,223],"slice-level":[132],"global":[133],"models":[134],"more":[136],"robust":[137],"against":[138],"noise":[139],"voxel-level":[142],"models.":[144],"Further,":[145],"used":[147,165],"log-determinant":[149],"covariant":[151],"as":[153],"non-convex":[155],"surrogate":[156,173],"penalty":[160],"instead":[161],"widely":[164],"convex":[166],"surrogates.":[167],"We":[168],"demonstrated":[169],"that":[170,228],"adopted":[172],"essentially":[174],"near-optimal":[176],"sparsity":[177],"underlying":[180],"principal":[181],"component":[182],"analysis":[183],"(PCA)":[184],"domain":[185],"without":[186],"explicit":[187],"training.":[188],"Apparently,":[189],"LACS":[190,207],"does":[191],"not":[192],"rely":[193],"on":[194,201],"any":[195],"ground-truth":[196],"training":[197],"data.":[198],"When":[199],"tested":[200],"a":[202,238],"real-world":[203],"dataset,":[206],"significantly":[208],"improved":[209],"quality":[211],"maps":[215],"using":[216],"just":[217],"one":[218],"pair":[219],"L/C":[221,231],"images,":[222],"standard":[226],"pipeline":[227],"requires":[229],"multiple":[230],"pairs.":[232],"proposed":[234],"scheme":[235],"set":[237],"new":[239],"benchmark":[240],"denoising.":[244]},"counts_by_year":[],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2026-07-01T00:00:00"}
