{"id":"https://openalex.org/W4386350490","doi":"https://doi.org/10.1109/isbi53787.2023.10230775","title":"Leveraging High-Quality Research Data for Ischemic Stroke Lesion Segmentation on Clinical Data","display_name":"Leveraging High-Quality Research Data for Ischemic Stroke Lesion Segmentation on Clinical Data","publication_year":2023,"publication_date":"2023-04-18","ids":{"openalex":"https://openalex.org/W4386350490","doi":"https://doi.org/10.1109/isbi53787.2023.10230775"},"language":"en","primary_location":{"id":"doi:10.1109/isbi53787.2023.10230775","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi53787.2023.10230775","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 20th 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/A5069856930","display_name":"Michal Brzus","orcid":"https://orcid.org/0000-0003-4236-311X"},"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":true,"raw_author_name":"Michal Brzus","raw_affiliation_strings":["The University of Iowa,Department of Electrical and Computer Engineering,Iowa City,IA","Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA"],"affiliations":[{"raw_affiliation_string":"The University of Iowa,Department of Electrical and Computer Engineering,Iowa City,IA","institution_ids":["https://openalex.org/I126307644"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077179906","display_name":"Aaron D. Boes","orcid":"https://orcid.org/0000-0002-7865-9257"},"institutions":[{"id":"https://openalex.org/I4210101492","display_name":"Carver Bible College","ror":"https://ror.org/01029e417","country_code":"US","type":"education","lineage":["https://openalex.org/I4210101492"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aaron D. Boes","raw_affiliation_strings":["Carver College of Medicine,Department of Neurology","Department of Neurology, Carver College of Medicine"],"affiliations":[{"raw_affiliation_string":"Carver College of Medicine,Department of Neurology","institution_ids":["https://openalex.org/I4210101492"]},{"raw_affiliation_string":"Department of Neurology, Carver College of Medicine","institution_ids":["https://openalex.org/I4210101492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023847206","display_name":"Joel Bruss","orcid":"https://orcid.org/0000-0003-2415-1658"},"institutions":[{"id":"https://openalex.org/I4210101492","display_name":"Carver Bible College","ror":"https://ror.org/01029e417","country_code":"US","type":"education","lineage":["https://openalex.org/I4210101492"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joel Bruss","raw_affiliation_strings":["Carver College of Medicine,Department of Neurology","Department of Neurology, Carver College of Medicine"],"affiliations":[{"raw_affiliation_string":"Carver College of Medicine,Department of Neurology","institution_ids":["https://openalex.org/I4210101492"]},{"raw_affiliation_string":"Department of Neurology, Carver College of Medicine","institution_ids":["https://openalex.org/I4210101492"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084167572","display_name":"Hans J. Johnson","orcid":"https://orcid.org/0000-0001-9513-2660"},"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":"Hans J. Johnson","raw_affiliation_strings":["The University of Iowa,Department of Electrical and Computer Engineering,Iowa City,IA","Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA"],"affiliations":[{"raw_affiliation_string":"The University of Iowa,Department of Electrical and Computer Engineering,Iowa City,IA","institution_ids":["https://openalex.org/I126307644"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA","institution_ids":["https://openalex.org/I126307644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5069856930"],"corresponding_institution_ids":["https://openalex.org/I126307644"],"apc_list":null,"apc_paid":null,"fwci":0.6639,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.72184393,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"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/T10227","display_name":"Acute Ischemic Stroke Management","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/T10227","display_name":"Acute Ischemic Stroke Management","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9969000220298767,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8047795295715332},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6755973696708679},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6579010486602783},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6545864343643188},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5269057154655457},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.4830913543701172},{"id":"https://openalex.org/keywords/market-segmentation","display_name":"Market segmentation","score":0.4799654483795166},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.475847452878952},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.4568110704421997},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.45214682817459106},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.45005959272384644},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.43502938747406006},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3979032337665558},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35699838399887085}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8047795295715332},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6755973696708679},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6579010486602783},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6545864343643188},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5269057154655457},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.4830913543701172},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.4799654483795166},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.475847452878952},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.4568110704421997},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.45214682817459106},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.45005959272384644},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.43502938747406006},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3979032337665558},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35699838399887085},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi53787.2023.10230775","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi53787.2023.10230775","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4000000059604645}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1909740415","https://openalex.org/W1987869189","https://openalex.org/W2066579873","https://openalex.org/W2160952634","https://openalex.org/W2912684384","https://openalex.org/W3125779006","https://openalex.org/W4285097303","https://openalex.org/W4295312788","https://openalex.org/W4308610041","https://openalex.org/W4311663126","https://openalex.org/W4320919371","https://openalex.org/W6766978945","https://openalex.org/W6846418509"],"related_works":["https://openalex.org/W3202554610","https://openalex.org/W2186437798","https://openalex.org/W138569904","https://openalex.org/W176219849","https://openalex.org/W3021414116","https://openalex.org/W3081133439","https://openalex.org/W2380699730","https://openalex.org/W1557144543","https://openalex.org/W4386246791","https://openalex.org/W2945537679"],"abstract_inverted_index":{"Modern":[0],"Deep":[1,87],"Learning":[2,88],"models":[3,41,89],"are":[4,26,206],"often":[5],"developed,":[6],"tuned,":[7],"and":[8,52,110,183],"reported":[9],"for":[10,69,82,90],"extremely":[11],"high-quality":[12,137],"research":[13,80,138,156],"data.":[14,97],"Unfortunately,":[15],"due":[16],"to":[17,30,42,77,128,140,158,170,180,192,208],"constraints":[18],"of":[19,34,54,86,103,122,154],"the":[20,43,50,84,120,123,165,185],"clinical":[21,44,72,96,131,160,212],"environments,":[22],"much":[23],"lower-quality":[24],"data":[25,81,139,157],"routinely":[27],"acquired,":[28],"leading":[29],"a":[31,141,152,211],"slow":[32],"adaptation":[33],"segmentation":[35,66],"models.":[36,56],"Applying":[37],"new":[38],"deep":[39],"learning":[40],"domain":[45],"requires":[46],"special":[47],"care":[48],"in":[49,63,119,201,210],"training":[51,118,142],"deployment":[53],"those":[55],"This":[57],"work":[58],"will":[59],"guide":[60],"model":[61,108,166],"developers":[62],"creating":[64],"image":[65],"tools":[67],"suitable":[68],"currently":[70],"collected":[71],"data.Specifically,":[73],"we":[74,150,196],"identify":[75],"strategies":[76],"utilize":[78],"high-resolution":[79],"improving":[83],"performance":[85,147,167,199],"segmenting":[91,202],"ischemic":[92],"stroke":[93],"lesions":[94],"on":[95],"We":[98],"analyze":[99],"how":[100,111],"improper":[101],"manipulation":[102],"binary":[104],"masks":[105],"negatively":[106],"affects":[107],"training,":[109],"carefully":[112],"constructed":[113],"preprocessing":[114],"steps":[115],"allow":[116],"improved":[117,130],"context":[121],"widely":[124],"accepted":[125],"3D-UNet":[126],"architectures":[127],"achieve":[129],"performance.We":[132],"demonstrate":[133],"that":[134,162],"naively":[135],"adding":[136],"dataset":[143],"does":[144],"not":[145],"ensure":[146],"improvement":[148,200],"However,":[149],"propose":[151],"method":[153],"manipulating":[155],"resemble":[159],"scans":[161],"significantly":[163],"improves":[164],"from":[168,190],"0.64":[169],"0.70":[171],"Dice":[172],"coefficient.":[173],"Our":[174],"solution":[175],"was":[176],"also":[177],"more":[178],"robust":[179],"false":[181],"positives":[182],"decreased":[184],"balanced":[186],"averaged":[187],"Hausdorff":[188],"distance":[189],"0.508":[191],"0.305":[193],"voxels.":[194],"Additionally,":[195],"observed":[197],"substantial":[198],"small":[203],"lesions,":[204],"which":[205],"difficult":[207],"capture":[209],"setting.":[213]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}