{"id":"https://openalex.org/W7161246914","doi":"https://doi.org/10.1016/j.knosys.2026.116200","title":"EfficientMedFormer: A directional decomposition approach for lightweight medical image classification","display_name":"EfficientMedFormer: A directional decomposition approach for lightweight medical image classification","publication_year":2026,"publication_date":"2026-05-15","ids":{"openalex":"https://openalex.org/W7161246914","doi":"https://doi.org/10.1016/j.knosys.2026.116200"},"language":"en","primary_location":{"id":"doi:10.1016/j.knosys.2026.116200","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.knosys.2026.116200","pdf_url":null,"source":{"id":"https://openalex.org/S10169007","display_name":"Knowledge-Based Systems","issn_l":"0950-7051","issn":["0950-7051","1872-7409"],"is_oa":false,"is_in_doaj":false,"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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge-Based Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.knosys.2026.116200","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136272340","display_name":"Seongchan Park","orcid":"https://orcid.org/0009-0008-0577-2436"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seongchan Park","raw_affiliation_strings":["Department of Plasma Bio Display, Kwangwoon University, Seoul, 01897, South Korea"],"raw_orcid":"https://orcid.org/0009-0008-0577-2436","affiliations":[{"raw_affiliation_string":"Department of Plasma Bio Display, Kwangwoon University, Seoul, 01897, South Korea","institution_ids":["https://openalex.org/I161024014"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061730987","display_name":"\uae40\uc9c4\ube48","orcid":null},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jinbin Kim","raw_affiliation_strings":["Department of Plasma Bio Display, Kwangwoon University, Seoul, 01897, South Korea"],"raw_orcid":"https://orcid.org/0009-0002-0743-2386","affiliations":[{"raw_affiliation_string":"Department of Plasma Bio Display, Kwangwoon University, Seoul, 01897, South Korea","institution_ids":["https://openalex.org/I161024014"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136257954","display_name":"Seunghyun Lee","orcid":"https://orcid.org/0000-0002-4113-5118"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seunghyun Lee","raw_affiliation_strings":["Department of Liberal Arts, Ingenium College, Kwangwoon University, Seoul, 01897, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-4113-5118","affiliations":[{"raw_affiliation_string":"Department of Liberal Arts, Ingenium College, Kwangwoon University, Seoul, 01897, South Korea","institution_ids":["https://openalex.org/I161024014"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044901165","display_name":"Soonchul Kwon","orcid":"https://orcid.org/0000-0001-6595-6415"},"institutions":[{"id":"https://openalex.org/I161024014","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863","country_code":"KR","type":"education","lineage":["https://openalex.org/I161024014"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Soonchul Kwon","raw_affiliation_strings":["Department of Interdisciplinary Information Systems, Graduate School of Smart Convergence, Kwangwoon University, Seoul, 01897, South Korea"],"raw_orcid":"https://orcid.org/0000-0001-6595-6415","affiliations":[{"raw_affiliation_string":"Department of Interdisciplinary Information Systems, Graduate School of Smart Convergence, Kwangwoon University, Seoul, 01897, South Korea","institution_ids":["https://openalex.org/I161024014"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5044901165"],"corresponding_institution_ids":["https://openalex.org/I161024014"],"apc_list":{"value":3130,"currency":"USD","value_usd":3130},"apc_paid":{"value":3130,"currency":"USD","value_usd":3130},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.94834906,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":"346","issue":null,"first_page":"116200","last_page":"116200"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.13220000267028809,"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":0.13220000267028809,"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/T10057","display_name":"Face and Expression Recognition","score":0.08609999716281891,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.0851999968290329,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4092999994754791},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40560001134872437},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.33980000019073486},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.31630000472068787},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.3138999938964844},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.31209999322891235}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6480000019073486},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5776000022888184},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5680000185966492},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4092999994754791},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40560001134872437},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.33980000019073486},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.31630000472068787},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.3138999938964844},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.31209999322891235},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.28529998660087585},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2752000093460083},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.26570001244544983},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.26249998807907104},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.knosys.2026.116200","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.knosys.2026.116200","pdf_url":null,"source":{"id":"https://openalex.org/S10169007","display_name":"Knowledge-Based Systems","issn_l":"0950-7051","issn":["0950-7051","1872-7409"],"is_oa":false,"is_in_doaj":false,"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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge-Based Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1016/j.knosys.2026.116200","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.knosys.2026.116200","pdf_url":null,"source":{"id":"https://openalex.org/S10169007","display_name":"Knowledge-Based Systems","issn_l":"0950-7051","issn":["0950-7051","1872-7409"],"is_oa":false,"is_in_doaj":false,"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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Knowledge-Based Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321374","display_name":"Kwangwoon University","ror":"https://ror.org/02e9zc863"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W3014974815","https://openalex.org/W3081500256","https://openalex.org/W3106819668","https://openalex.org/W3126423324","https://openalex.org/W3175515048","https://openalex.org/W3201701662","https://openalex.org/W4205271301","https://openalex.org/W4226244266","https://openalex.org/W4315607730","https://openalex.org/W4317436377","https://openalex.org/W4324144441","https://openalex.org/W4388145401","https://openalex.org/W4389633843","https://openalex.org/W4391697051","https://openalex.org/W4400721967","https://openalex.org/W4406887277","https://openalex.org/W4408220982","https://openalex.org/W4410015669","https://openalex.org/W4414222762"],"related_works":[],"abstract_inverted_index":{"Medical":[0],"artificial":[1,241],"intelligence":[2,242],"is":[3,22],"advancing":[4,235],"rapidly":[5],"and":[6,13,37,80,131,139,152,182,203,228,270,281],"contributing":[7],"significantly":[8,103],"to":[9],"the":[10,61,84,88,90,115,118,137,170,177,225,231,236],"early":[11,85],"detection":[12],"accurate":[14],"diagnosis":[15],"of":[16,87,191,211,230,239,257],"diseases.":[17],"Although":[18],"medical":[19,171,240,251],"image":[20,252],"classification":[21,174],"crucial":[23],"in":[24,30,114,169],"this":[25,44,196],"diagnostic":[26],"process,":[27],"its":[28],"application":[29],"real-world":[31],"clinical":[32,237],"environments":[33],"demands":[34],"high":[35,226,264],"accuracy":[36,190],"computational":[38,105,260],"efficiency.":[39],"To":[40],"address":[41],"these":[42],"requirements,":[43],"paper":[45],"proposes":[46],"EfficientMedFormer,":[47],"a":[48,66,73,109,188],"novel":[49,246],"lightweight":[50,247],"hybrid":[51,248],"architecture":[52,249],"that":[53],"integrates":[54],"an":[55,208,215],"anisotropic":[56,69,91,121],"convolutional":[57,92],"block":[58,93],"based":[59],"on":[60,176,214,277,291],"directional":[62,98],"decomposition":[63,256],"principle":[64],"with":[65,165,199,266],"gated":[67,119],"channel-wise":[68,120],"attention":[70,122,127],"module":[71,123],"within":[72],"progressive":[74],"hierarchical":[75],"structure,":[76],"effectively":[77,148],"fusing":[78],"local":[79],"global":[81,154],"features.":[82],"In":[83],"stages":[86],"model,":[89,233],"decomposes":[94],"standard":[95],"convolutions":[96],"into":[97],"one-dimensional":[99],"convolutions.":[100],"This":[101,142],"approach":[102],"reduces":[104],"cost":[106],"while":[107,206],"maintaining":[108],"wide":[110],"receptive":[111],"field.":[112],"Subsequently,":[113],"later":[116],"stages,":[117],"enhances":[124],"conventional":[125],"channel":[126,146],"by":[128],"independently":[129],"extracting":[130],"directly":[132],"gating":[133],"contextual":[134],"information":[135,151],"along":[136],"height":[138],"width":[140],"directions.":[141],"mechanism":[143],"dynamically":[144],"reweights":[145],"importance,":[147],"preserving":[149],"spatial":[150],"modeling":[153],"relationships.":[155],"The":[156],"proposed":[157,232],"model":[158],"achieves":[159],"comparable":[160],"or":[161],"superior":[162],"performance":[163,198,265,276],"compared":[164],"widely":[166],"used":[167],"models":[168],"domain":[172],"across":[173],"tasks":[175],"MedMNIST":[178],"v2,":[179],"PAD-UFES-20,":[180],"Kvasir,":[181,279],"Brain":[183,282],"Tumor":[184,283],"MRI":[185,284],"datasets,":[186],"achieving":[187],"maximum":[189],"99%.":[192],"Notably,":[193],"EfficientMedFormer":[194],"attains":[195],"top-tier":[197,288],"only":[200,267],"2.39M":[201,268],"parameters":[202,269],"0.28":[204,271],"GFLOPs,":[205],"demonstrating":[207],"inference":[209,289],"latency":[210],"74.6":[212],"ms":[213],"Orange":[216],"Pi":[217],"5B":[218],"edge":[219],"device":[220],"These":[221],"quantitative":[222],"results":[223],"underscore":[224],"practicality":[227],"generalizability":[229],"thereby":[234],"applicability":[238],"systems.":[243],"\u2022":[244,254,262,273,286],"A":[245],"for":[250],"classification.":[253],"Directional":[255],"operations":[258],"minimizes":[259],"costs.":[261],"Achieves":[263],"GFLOPs.":[272],"Shows":[274],"SOTA":[275],"MedMNIST,":[278],"PAD-UFES-20":[280],"datasets.":[285],"Demonstrates":[287],"speeds":[290],"various":[292],"embedded":[293],"devices.":[294]},"counts_by_year":[],"updated_date":"2026-05-17T06:04:21.649783","created_date":"2026-05-16T00:00:00"}