{"id":"https://openalex.org/W4401749153","doi":"https://doi.org/10.1109/isbi56570.2024.10635343","title":"Assessing Test-Time Variability for Interactive 3D Medical Image Segmentation with Diverse Point Prompts","display_name":"Assessing Test-Time Variability for Interactive 3D Medical Image Segmentation with Diverse Point Prompts","publication_year":2024,"publication_date":"2024-05-27","ids":{"openalex":"https://openalex.org/W4401749153","doi":"https://doi.org/10.1109/isbi56570.2024.10635343"},"language":"en","primary_location":{"id":"doi:10.1109/isbi56570.2024.10635343","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi56570.2024.10635343","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 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/A5100348588","display_name":"Hao Li","orcid":"https://orcid.org/0000-0002-4019-3420"},"institutions":[{"id":"https://openalex.org/I200719446","display_name":"Vanderbilt University","ror":"https://ror.org/02vm5rt34","country_code":"US","type":"education","lineage":["https://openalex.org/I200719446"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hao Li","raw_affiliation_strings":["Vanderbilt University"],"affiliations":[{"raw_affiliation_string":"Vanderbilt University","institution_ids":["https://openalex.org/I200719446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032692212","display_name":"Han Liu","orcid":"https://orcid.org/0000-0002-4756-7149"},"institutions":[{"id":"https://openalex.org/I200719446","display_name":"Vanderbilt University","ror":"https://ror.org/02vm5rt34","country_code":"US","type":"education","lineage":["https://openalex.org/I200719446"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Han Liu","raw_affiliation_strings":["Vanderbilt University"],"affiliations":[{"raw_affiliation_string":"Vanderbilt University","institution_ids":["https://openalex.org/I200719446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055020146","display_name":"Dewei Hu","orcid":"https://orcid.org/0000-0001-7203-4136"},"institutions":[{"id":"https://openalex.org/I200719446","display_name":"Vanderbilt University","ror":"https://ror.org/02vm5rt34","country_code":"US","type":"education","lineage":["https://openalex.org/I200719446"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dewei Hu","raw_affiliation_strings":["Vanderbilt University"],"affiliations":[{"raw_affiliation_string":"Vanderbilt University","institution_ids":["https://openalex.org/I200719446"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100727959","display_name":"Jiacheng Wang","orcid":"https://orcid.org/0000-0003-1252-8761"},"institutions":[{"id":"https://openalex.org/I200719446","display_name":"Vanderbilt University","ror":"https://ror.org/02vm5rt34","country_code":"US","type":"education","lineage":["https://openalex.org/I200719446"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiacheng Wang","raw_affiliation_strings":["Vanderbilt University"],"affiliations":[{"raw_affiliation_string":"Vanderbilt University","institution_ids":["https://openalex.org/I200719446"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020532873","display_name":"\u0130pek O\u011fuz","orcid":"https://orcid.org/0000-0002-1403-2420"},"institutions":[{"id":"https://openalex.org/I200719446","display_name":"Vanderbilt University","ror":"https://ror.org/02vm5rt34","country_code":"US","type":"education","lineage":["https://openalex.org/I200719446"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ipek Oguz","raw_affiliation_strings":["Vanderbilt University"],"affiliations":[{"raw_affiliation_string":"Vanderbilt University","institution_ids":["https://openalex.org/I200719446"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100348588"],"corresponding_institution_ids":["https://openalex.org/I200719446"],"apc_list":null,"apc_paid":null,"fwci":1.8369,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.86651722,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9986000061035156,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9975000023841858,"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/T10862","display_name":"AI in cancer detection","score":0.9908999800682068,"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/computer-science","display_name":"Computer science","score":0.6880229711532593},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6499846577644348},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.571894109249115},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.5563592910766602},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5234740972518921},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48500534892082214},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4803149104118347},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4363621473312378},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.3308648467063904},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10106676816940308}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6880229711532593},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6499846577644348},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.571894109249115},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.5563592910766602},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5234740972518921},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48500534892082214},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4803149104118347},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4363621473312378},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.3308648467063904},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10106676816940308},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi56570.2024.10635343","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi56570.2024.10635343","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 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":23,"referenced_works":["https://openalex.org/W2763160469","https://openalex.org/W3034550159","https://openalex.org/W3035485193","https://openalex.org/W3172681723","https://openalex.org/W3214085799","https://openalex.org/W4312713789","https://openalex.org/W4362603500","https://openalex.org/W4367189325","https://openalex.org/W4367692241","https://openalex.org/W4382131005","https://openalex.org/W4385211211","https://openalex.org/W4386081369","https://openalex.org/W4389213130","https://openalex.org/W4390872651","https://openalex.org/W4390874575","https://openalex.org/W4390971106","https://openalex.org/W4391109864","https://openalex.org/W4391465094","https://openalex.org/W4401749938","https://openalex.org/W6851970734","https://openalex.org/W6851980744","https://openalex.org/W6853207815","https://openalex.org/W6855944785"],"related_works":["https://openalex.org/W4379231730","https://openalex.org/W4389858081","https://openalex.org/W2501551404","https://openalex.org/W4385583601","https://openalex.org/W4298131179","https://openalex.org/W2113201962","https://openalex.org/W4395685956","https://openalex.org/W2799953226","https://openalex.org/W4398146871","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Interactive":[0],"segmentation":[1,56,81,154],"model":[2],"leverages":[3],"prompts":[4,20],"from":[5],"users":[6],"to":[7,50,105],"produce":[8],"robust":[9],"segmentation.":[10],"This":[11,58],"advancement":[12],"is":[13,29,93,104,172],"facilitated":[14],"by":[15,167],"prompt":[16,52,114,130,137,162],"engineering,":[17],"where":[18],"interactive":[19,78],"serve":[21],"as":[22],"strong":[23],"priors":[24],"during":[25,116,164],"test-time.":[26],"However,":[27],"this":[28,70],"an":[30,158],"inherently":[31,42],"subjective":[32],"and":[33,41,100,109,132],"hard-to-reproduce":[34],"process.":[35],"The":[36,170],"variability":[37,76],"in":[38,45],"user":[39],"expertise":[40],"ambiguous":[43],"boundaries":[44],"medical":[46,67,79],"images":[47],"can":[48],"lead":[49],"inconsistent":[51],"selections,":[53],"potentially":[54],"affecting":[55],"accuracy.":[57],"issue":[59],"has":[60],"not":[61],"yet":[62],"been":[63],"extensively":[64],"explored":[65],"for":[66,77,112,135,150,161],"imaging.":[68],"In":[69],"paper,":[71],"we":[72],"assess":[73],"the":[74,91,144],"test-time":[75,117],"image":[80],"with":[82],"diverse":[83],"point":[84,92],"prompts.":[85],"For":[86],"a":[87,107],"given":[88],"target":[89],"region,":[90],"classified":[94],"into":[95],"three":[96,120],"sub-regions:":[97],"boundary,":[98],"margin,":[99],"center.":[101],"Our":[102],"goal":[103],"identify":[106],"straightforward":[108],"efficient":[110],"approach":[111],"optimal":[113,136,159],"selection":[115,163],"based":[118],"on":[119,143],"considerations:":[121],"(1)":[122],"benefits":[123],"of":[124,129],"additional":[125],"prompts,":[126],"(2)":[127],"effects":[128],"placement,":[131],"(3)":[133],"strategies":[134],"selection.":[138],"We":[139,156],"conduct":[140],"extensive":[141],"experiments":[142],"public":[145],"Medical":[146],"Segmentation":[147],"Decathlon":[148],"dataset":[149],"challenging":[151],"colon":[152],"tumor":[153],"task.":[155],"suggest":[157],"strategy":[160],"test-time,":[165],"supported":[166],"comprehensive":[168],"results.":[169],"code":[171],"publicly":[173],"available":[174],"at":[175],"https://github.com/MedICL-VU/variability":[176]},"counts_by_year":[{"year":2024,"cited_by_count":7}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
