{"id":"https://openalex.org/W4410296342","doi":"https://doi.org/10.1109/isbi60581.2025.10981010","title":"Quantifying White Matter Hyperintensities: Predicting Periventricular Fazekas Scores with Uncertainty Estimation","display_name":"Quantifying White Matter Hyperintensities: Predicting Periventricular Fazekas Scores with Uncertainty Estimation","publication_year":2025,"publication_date":"2025-04-14","ids":{"openalex":"https://openalex.org/W4410296342","doi":"https://doi.org/10.1109/isbi60581.2025.10981010"},"language":"en","primary_location":{"id":"doi:10.1109/isbi60581.2025.10981010","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi60581.2025.10981010","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":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033060481","display_name":"Susanne Schmid","orcid":"https://orcid.org/0000-0001-5366-8061"},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Susanne Schmid","raw_affiliation_strings":["University of Calgary,Biomedical Engineering Graduate Program"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Calgary,Biomedical Engineering Graduate Program","institution_ids":["https://openalex.org/I168635309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5117518261","display_name":"Amirmohammed Shamaei","orcid":null},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]},{"id":"https://openalex.org/I97750245","display_name":"Software (Spain)","ror":"https://ror.org/02ethns06","country_code":"ES","type":"company","lineage":["https://openalex.org/I4210087817","https://openalex.org/I97750245"]}],"countries":["CA","ES"],"is_corresponding":false,"raw_author_name":"Amirmohammed Shamaei","raw_affiliation_strings":["University of Calgary,Electrical and Software Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Calgary,Electrical and Software Engineering","institution_ids":["https://openalex.org/I168635309","https://openalex.org/I97750245"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034139388","display_name":"Roberto Souza","orcid":"https://orcid.org/0000-0001-7824-5217"},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Roberto Souza","raw_affiliation_strings":["University of Calgary,Biomedical Engineering Graduate Program"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Calgary,Biomedical Engineering Graduate Program","institution_ids":["https://openalex.org/I168635309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085398611","display_name":"Richard Frayne","orcid":"https://orcid.org/0000-0003-0358-1210"},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Richard Frayne","raw_affiliation_strings":["University of Calgary,Biomedical Engineering Graduate Program"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Calgary,Biomedical Engineering Graduate Program","institution_ids":["https://openalex.org/I168635309"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15875343,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.29670000076293945,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.29670000076293945,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/T14393","display_name":"Health, Environment, Cognitive Aging","score":0.2827000021934509,"subfield":{"id":"https://openalex.org/subfields/2307","display_name":"Health, Toxicology and Mutagenesis"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.26589998602867126,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperintensity","display_name":"Hyperintensity","score":0.7736977338790894},{"id":"https://openalex.org/keywords/white-matter","display_name":"White matter","score":0.4284384250640869},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.21646636724472046},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.17049920558929443},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.05317968130111694}],"concepts":[{"id":"https://openalex.org/C146638467","wikidata":"https://www.wikidata.org/wiki/Q10529587","display_name":"Hyperintensity","level":3,"score":0.7736977338790894},{"id":"https://openalex.org/C2781192897","wikidata":"https://www.wikidata.org/wiki/Q822050","display_name":"White matter","level":3,"score":0.4284384250640869},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.21646636724472046},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.17049920558929443},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.05317968130111694}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi60581.2025.10981010","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi60581.2025.10981010","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2090103820","https://openalex.org/W3206072240","https://openalex.org/W2021468470","https://openalex.org/W2106430568","https://openalex.org/W2082419882","https://openalex.org/W2117421758","https://openalex.org/W1991894501","https://openalex.org/W2107764488","https://openalex.org/W2067113209","https://openalex.org/W3092209499"],"abstract_inverted_index":{"White":[0],"matter":[1],"hyperintensities":[2],"(WMH)":[3],"are":[4],"crucial":[5],"markers":[6],"in":[7,30],"brain":[8],"magnetic":[9],"resonance":[10],"(MR)":[11],"images,":[12],"often":[13],"quantified":[14],"using":[15,82],"the":[16,31,89],"Fazekas":[17,28,58],"score.":[18],"This":[19],"study":[20],"presents":[21],"a":[22,42,70],"deep":[23],"learning":[24],"model":[25,40],"to":[26,62],"predict":[27],"scores":[29,50,59],"periventricular":[32],"region":[33],"from":[34,60],"T1-weighted":[35],"and":[36,48,55,105],"FLAIR":[37],"images.":[38],"Our":[39],"achieved":[41],"Matthew":[43],"correlation":[44],"coefficient":[45],"of":[46,51,73,130],"0.68":[47],"F1":[49],"0.69,":[52],"0.88,":[53],"0.86,":[54],"1.0":[56],"for":[57],"0":[61],"3,":[63],"respectively,":[64],"surpassing":[65],"previous":[66],"methods.":[67],"We":[68],"introduce":[69],"novel":[71],"integration":[72],"t-distributed":[74],"stochastic":[75],"neighbor":[76],"embedding":[77],"(t-SNE)":[78],"with":[79,97,123],"uncertainty":[80,99],"analysis":[81],"Monte":[83],"Carlo":[84],"dropout,":[85],"offering":[86],"insights":[87],"into":[88],"model's":[90],"decision-making.":[91],"Results":[92],"show":[93],"effective":[94],"class":[95,101],"distinction,":[96],"increased":[98],"at":[100],"transitions":[102],"indicating":[103],"ambiguity,":[104],"confident":[106],"misclassified":[107],"cases":[108],"suggesting":[109],"overlapping":[110],"features":[111],"or":[112],"label":[113],"noise.":[114],"These":[115],"findings":[116],"highlight":[117],"that":[118],"simple,":[119],"well-tuned":[120],"models,":[121],"coupled":[122],"interpretability":[124],"techniques,":[125],"can":[126],"provide":[127],"robust":[128],"predictions":[129],"WMH":[131],"severity.":[132]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}