{"id":"https://openalex.org/W7125399070","doi":"https://doi.org/10.48550/arxiv.2601.15119","title":"Vision Models for Medical Imaging: A Hybrid Approach for PCOS Detection from Ultrasound Scans","display_name":"Vision Models for Medical Imaging: A Hybrid Approach for PCOS Detection from Ultrasound Scans","publication_year":2026,"publication_date":"2026-01-21","ids":{"openalex":"https://openalex.org/W7125399070","doi":"https://doi.org/10.48550/arxiv.2601.15119"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.15119","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.15119","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2601.15119","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123616399","display_name":"Md Mahmudul Hoque","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hoque, Md Mahmudul","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5095828819","display_name":"Md Mehedi Hassain","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hassain, Md Mehedi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123575262","display_name":"Muntakimur Rahaman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rahaman, Muntakimur","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123543407","display_name":"Md. Towhidul Islam","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Islam, Md. Towhidul","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017538801","display_name":"Shaista Rani","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rani, Shaista","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5023736122","display_name":"Md.Anhar Sharif Mollah","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mollah, Md Sharif","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10390","display_name":"Ovarian function and disorders","score":0.6485000252723694,"subfield":{"id":"https://openalex.org/subfields/2743","display_name":"Reproductive 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/T10390","display_name":"Ovarian function and disorders","score":0.6485000252723694,"subfield":{"id":"https://openalex.org/subfields/2743","display_name":"Reproductive 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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.018699999898672104,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.01549999974668026,"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/polycystic-ovary","display_name":"Polycystic ovary","score":0.7731999754905701},{"id":"https://openalex.org/keywords/ultrasound","display_name":"Ultrasound","score":0.48489999771118164},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.3368000090122223},{"id":"https://openalex.org/keywords/hybrid-system","display_name":"Hybrid system","score":0.32429999113082886},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32190001010894775},{"id":"https://openalex.org/keywords/ultrasound-imaging","display_name":"Ultrasound imaging","score":0.3050999939441681},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.3025999963283539}],"concepts":[{"id":"https://openalex.org/C3018442814","wikidata":"https://www.wikidata.org/wiki/Q500816","display_name":"Polycystic ovary","level":4,"score":0.7731999754905701},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.5601999759674072},{"id":"https://openalex.org/C143753070","wikidata":"https://www.wikidata.org/wiki/Q162564","display_name":"Ultrasound","level":2,"score":0.48489999771118164},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45329999923706055},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4507000148296356},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.3368000090122223},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.32429999113082886},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32190001010894775},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31360000371932983},{"id":"https://openalex.org/C2986892559","wikidata":"https://www.wikidata.org/wiki/Q234904","display_name":"Ultrasound imaging","level":3,"score":0.3050999939441681},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.3025999963283539},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.29980000853538513},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2992999851703644},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.2921999990940094},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2870999872684479},{"id":"https://openalex.org/C3020132585","wikidata":"https://www.wikidata.org/wiki/Q2671652","display_name":"Diagnostic accuracy","level":2,"score":0.28049999475479126},{"id":"https://openalex.org/C529618451","wikidata":"https://www.wikidata.org/wiki/Q234904","display_name":"Ultrasonography","level":2,"score":0.2793999910354614},{"id":"https://openalex.org/C29456083","wikidata":"https://www.wikidata.org/wiki/Q1221899","display_name":"Gynecology","level":1,"score":0.26440000534057617},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2540000081062317},{"id":"https://openalex.org/C2992165143","wikidata":"https://www.wikidata.org/wiki/Q234904","display_name":"Medical ultrasound","level":3,"score":0.2531000077724457},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.15119","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.15119","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2601.15119","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.15119","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Gender equality","id":"https://metadata.un.org/sdg/5","score":0.5037616491317749},{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.4965240955352783}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Polycystic":[0],"Ovary":[1],"Syndrome":[2],"(PCOS)":[3],"is":[4,31],"the":[5,45,78,120],"most":[6],"familiar":[7],"endocrine":[8],"illness":[9],"in":[10,22],"women":[11,17],"of":[12,28,48],"reproductive":[13],"age.":[14,25],"Many":[15],"Bangladeshi":[16],"suffer":[18],"from":[19,132],"PCOS":[20,130],"disease":[21],"their":[23],"older":[24],"The":[26,61,95],"aim":[27],"our":[29,81],"research":[30,124],"to":[32],"identify":[33],"effective":[34],"vision-based":[35],"medical":[36],"image":[37],"analysis":[38],"techniques":[39],"and":[40,58,63,73,90,106],"evaluate":[41],"hybrid":[42,54,83],"models":[43,55],"for":[44,129],"accurate":[46],"detection":[47,131,141],"PCOS.":[49],"We":[50],"introduced":[51],"two":[52,69],"novel":[53],"combining":[56],"convolutional":[57],"transformer-based":[59],"approaches.":[60],"training":[62],"testing":[64],"data":[65],"were":[66],"organized":[67],"into":[68],"categories:":[70],"\"infected\"":[71],"(PCOS-positive)":[72],"\"noninfected\"":[74],"(healthy":[75],"ovaries).":[76],"In":[77],"initial":[79],"stage,":[80],"first":[82],"model,":[84,98],"'DenConST'":[85],"(integrating":[86],"DenseNet121,":[87,104],"Swin":[88,101],"Transformer,":[89,102],"ConvNeXt),":[91],"achieved":[92],"85.69%":[93],"accuracy.":[94,113],"final":[96],"optimized":[97],"'DenConREST'":[99],"(incorporating":[100],"ConvNeXt,":[103],"ResNet18,":[105],"EfficientNetV2),":[107],"demonstrated":[108],"superior":[109],"performance":[110],"with":[111],"98.23%":[112],"Among":[114],"all":[115],"evaluated":[116],"models,":[117],"DenConREST":[118],"showed":[119],"best":[121],"performance.":[122],"This":[123],"highlights":[125],"an":[126],"efficient":[127],"solution":[128],"ultrasound":[133],"images,":[134],"significantly":[135],"improving":[136],"diagnostic":[137],"accuracy":[138],"while":[139],"reducing":[140],"errors.":[142]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-01-23T00:00:00"}
