{"id":"https://openalex.org/W4308234197","doi":"https://doi.org/10.1109/icip46576.2022.9897966","title":"Using Vision Transformers in 3-D Medical Image Classifications","display_name":"Using Vision Transformers in 3-D Medical Image Classifications","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4308234197","doi":"https://doi.org/10.1109/icip46576.2022.9897966"},"language":"en","primary_location":{"id":"doi:10.1109/icip46576.2022.9897966","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897966","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5089925207","display_name":"Lulu Gai","orcid":null},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lulu Gai","raw_affiliation_strings":["Shandong University,School of Control Science and Engineering,Jinan,P.R. China,250100"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong University,School of Control Science and Engineering,Jinan,P.R. China,250100","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100344369","display_name":"Wei Chen","orcid":"https://orcid.org/0009-0000-5168-6645"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Chen","raw_affiliation_strings":["Shandong University,Department of Stomatology,Jinan,P.R. China,250012"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong University,Department of Stomatology,Jinan,P.R. China,250012","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080648360","display_name":"Rui Gao","orcid":"https://orcid.org/0000-0002-8476-0925"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Gao","raw_affiliation_strings":["Shandong University,School of Control Science and Engineering,Jinan,P.R. China,250100"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong University,School of Control Science and Engineering,Jinan,P.R. China,250100","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101563071","display_name":"Yanwei Chen","orcid":"https://orcid.org/0000-0002-2150-0827"},"institutions":[{"id":"https://openalex.org/I135768898","display_name":"Ritsumeikan University","ror":"https://ror.org/0197nmd03","country_code":"JP","type":"education","lineage":["https://openalex.org/I135768898","https://openalex.org/I4390039241"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yan-Wei Chen","raw_affiliation_strings":["Ritsumeikan University,College of Science and Engineering","College of Science and Engineering, Ritsumeikan University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ritsumeikan University,College of Science and Engineering","institution_ids":["https://openalex.org/I135768898"]},{"raw_affiliation_string":"College of Science and Engineering, Ritsumeikan University","institution_ids":["https://openalex.org/I135768898"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074871054","display_name":"Xu Qiao","orcid":null},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Qiao","raw_affiliation_strings":["Shandong University,School of Control Science and Engineering,Jinan,P.R. China,250100"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shandong University,School of Control Science and Engineering,Jinan,P.R. China,250100","institution_ids":["https://openalex.org/I154099455"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"696","last_page":"700"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9980999827384949,"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/T10862","display_name":"AI in cancer detection","score":0.9975000023841858,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7984780073165894},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7760950326919556},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7754507064819336},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.6026266813278198},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5775009393692017},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5562065243721008},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.48481789231300354},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4560723900794983},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4556472897529602},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4495113492012024},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.44566383957862854},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4191983640193939},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.40738314390182495},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39927560091018677},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09308099746704102}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7984780073165894},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7760950326919556},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7754507064819336},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.6026266813278198},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5775009393692017},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5562065243721008},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.48481789231300354},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4560723900794983},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4556472897529602},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4495113492012024},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.44566383957862854},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4191983640193939},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.40738314390182495},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39927560091018677},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09308099746704102},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip46576.2022.9897966","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897966","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","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":24,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W2108598243","https://openalex.org/W2895798907","https://openalex.org/W2947706148","https://openalex.org/W2970370255","https://openalex.org/W2970868609","https://openalex.org/W3012412627","https://openalex.org/W3026637813","https://openalex.org/W3037492894","https://openalex.org/W3094502228","https://openalex.org/W3139833881","https://openalex.org/W3159481202","https://openalex.org/W3168489096","https://openalex.org/W3193873731","https://openalex.org/W3194417301","https://openalex.org/W4288404646","https://openalex.org/W6757555829","https://openalex.org/W6762718338","https://openalex.org/W6763301180","https://openalex.org/W6777714645","https://openalex.org/W6784333009","https://openalex.org/W6788135285","https://openalex.org/W6796289114","https://openalex.org/W6799920274"],"related_works":["https://openalex.org/W2952813363","https://openalex.org/W2911497689","https://openalex.org/W4360783045","https://openalex.org/W4323287533","https://openalex.org/W2963346891","https://openalex.org/W2770149305","https://openalex.org/W2972076240","https://openalex.org/W3167930666","https://openalex.org/W3014952856","https://openalex.org/W2964843961"],"abstract_inverted_index":{"Convolutional":[0],"Neural":[1],"Networks":[2],"(CNNs)":[3],"have":[4,23],"been":[5],"the":[6,51,100,111,172],"controlling":[7],"deep":[8,54],"learning":[9,165],"approach":[10],"for":[11,50,119],"a":[12,26,128],"decade":[13],"in":[14,31,69,99,127],"automated":[15],"medical":[16,59,104,120,135],"image":[17,105,121,136],"diagnosis.":[18],"Recently,":[19],"vision":[20],"transformers":[21],"(ViTs)":[22],"appeared":[24],"as":[25],"competitive":[27],"alternative":[28],"to":[29,47,86,88,117],"CNNs":[30,98,143],"computer":[32],"vision,":[33],"yielding":[34],"similar":[35],"levels":[36],"of":[37,53,64,102,115,130],"performance":[38],"while":[39,142],"possessing":[40],"several":[41],"interesting":[42],"properties":[43],"that":[44],"could":[45],"prove":[46],"be":[48],"beneficial":[49],"explanation":[52],"neural":[55],"networks.":[56],"Since":[57],"most":[58],"images":[60],"are":[61,74,110],"grayscale":[62],"scans":[63],"CT,":[65],"MRI,":[66],"etc.":[67],"and":[68,113,158,166],"3-dimensional":[70],"(3-D)":[71],"spaces,":[72],"which":[73],"highly":[75],"different":[76],"from":[77,148],"natural":[78],"images,":[79],"we":[80,93],"explore":[81],"whether":[82],"it":[83],"is":[84],"possible":[85],"move":[87],"transformer-based":[89],"models":[90],"or":[91],"if":[92],"should":[94],"keep":[95],"working":[96],"with":[97],"domain":[101],"3-D":[103,134],"classifi-cations.":[106],"If":[107],"so,":[108],"what":[109],"advantages":[112],"drawbacks":[114],"switching":[116],"ViTs":[118,150],"diagnosis?":[122],"We":[123],"consider":[124],"these":[125],"problems":[126],"series":[129],"experiments":[131],"on":[132,156,171],"three":[133],"datasets.":[137,174],"Our":[138],"findings":[139],"show":[140],"that,":[141],"perform":[144],"better":[145],"when":[146,154],"trained":[147],"scratch,":[149],"gain":[151],"strong":[152],"benifit":[153],"pre-trained":[155],"ImageNet":[157],"outperform":[159],"their":[160],"CNN":[161],"counterparts":[162],"using":[163],"self-supervised":[164],"sharpness-aware":[167],"minimizer":[168],"optimization":[169],"method":[170],"large":[173]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
