{"id":"https://openalex.org/W7124975544","doi":"https://doi.org/10.1109/cvmi66673.2025.11337802","title":"A Comparative Study of UNet and its Variants for Breast Cancer Tumor Segmentation","display_name":"A Comparative Study of UNet and its Variants for Breast Cancer Tumor Segmentation","publication_year":2025,"publication_date":"2025-10-12","ids":{"openalex":"https://openalex.org/W7124975544","doi":"https://doi.org/10.1109/cvmi66673.2025.11337802"},"language":null,"primary_location":{"id":"doi:10.1109/cvmi66673.2025.11337802","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvmi66673.2025.11337802","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Computer Vision and Machine Intelligence (CVMI)","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/A5123449039","display_name":"Darshan Dathiya","orcid":null},"institutions":[{"id":"https://openalex.org/I167751958","display_name":"Institute of Chemical Technology","ror":"https://ror.org/00ykac431","country_code":"IN","type":"education","lineage":["https://openalex.org/I167751958"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Darshan Dathiya","raw_affiliation_strings":["Institute of Chemical Technology,Mumbai,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Chemical Technology,Mumbai,India","institution_ids":["https://openalex.org/I167751958"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103937122","display_name":"Ajit Kumar","orcid":null},"institutions":[{"id":"https://openalex.org/I167751958","display_name":"Institute of Chemical Technology","ror":"https://ror.org/00ykac431","country_code":"IN","type":"education","lineage":["https://openalex.org/I167751958"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ajit Kumar","raw_affiliation_strings":["Institute of Chemical Technology,Mumbai,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Chemical Technology,Mumbai,India","institution_ids":["https://openalex.org/I167751958"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063846597","display_name":"Narayana Darapaneni","orcid":null},"institutions":[{"id":"https://openalex.org/I4210100400","display_name":"Northwestern University","ror":"https://ror.org/00m6w7z96","country_code":"PH","type":"education","lineage":["https://openalex.org/I4210100400"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Narayana Darapaneni","raw_affiliation_strings":["Northwestern University SPS,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northwestern University SPS,USA","institution_ids":["https://openalex.org/I4210100400"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.79859751,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.8632000088691711,"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"}},"topics":[{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.8632000088691711,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.032600000500679016,"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/T12994","display_name":"Infrared Thermography in Medicine","score":0.013799999840557575,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.7454000115394592},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6287000179290771},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.4848000109195709},{"id":"https://openalex.org/keywords/breast-tumor","display_name":"Breast tumor","score":0.4733000099658966},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.4607999920845032},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.42660000920295715},{"id":"https://openalex.org/keywords/ultrasound","display_name":"Ultrasound","score":0.37959998846054077}],"concepts":[{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.7454000115394592},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6287000179290771},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.5698999762535095},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.4848000109195709},{"id":"https://openalex.org/C2986637895","wikidata":"https://www.wikidata.org/wiki/Q953865","display_name":"Breast tumor","level":4,"score":0.4733000099658966},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.4607999920845032},{"id":"https://openalex.org/C143998085","wikidata":"https://www.wikidata.org/wiki/Q162555","display_name":"Oncology","level":1,"score":0.43700000643730164},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.42660000920295715},{"id":"https://openalex.org/C143753070","wikidata":"https://www.wikidata.org/wiki/Q162564","display_name":"Ultrasound","level":2,"score":0.37959998846054077},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.37779998779296875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3264999985694885},{"id":"https://openalex.org/C105951970","wikidata":"https://www.wikidata.org/wiki/Q1036748","display_name":"Loss function","level":4,"score":0.3206999897956848},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.31470000743865967},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.2793000042438507},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2615000009536743},{"id":"https://openalex.org/C2777423100","wikidata":"https://www.wikidata.org/wiki/Q1888238","display_name":"Breast ultrasound","level":5,"score":0.25839999318122864},{"id":"https://openalex.org/C2779013556","wikidata":"https://www.wikidata.org/wiki/Q181876","display_name":"Metastasis","level":3,"score":0.25699999928474426}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvmi66673.2025.11337802","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvmi66673.2025.11337802","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Computer Vision and Machine Intelligence (CVMI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.651495099067688,"display_name":"Good health and well-being"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320767","display_name":"University Grants Commission","ror":"https://ror.org/04p800546"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2774320778","https://openalex.org/W2910702843","https://openalex.org/W2991372685","https://openalex.org/W3197300698","https://openalex.org/W4283160212","https://openalex.org/W4283515755","https://openalex.org/W4302364789","https://openalex.org/W4311287841","https://openalex.org/W4382999383","https://openalex.org/W4393196614","https://openalex.org/W4399203790","https://openalex.org/W4402483647","https://openalex.org/W4402937008","https://openalex.org/W4404908318","https://openalex.org/W4408117563"],"related_works":[],"abstract_inverted_index":{"Breast":[0],"cancer":[1,59,124],"is":[2,21,71],"one":[3],"of":[4,47,57,68,97,101,116],"the":[5,33,40,55,82,93,113],"most":[6],"common":[7],"cancers":[8],"among":[9],"women":[10],"worldwide,":[11],"with":[12,103],"early":[13],"detection":[14],"significantly":[15],"increasing":[16],"survival":[17],"rates.":[18],"Ultrasound":[19],"image":[20],"a":[22],"widely":[23],"used":[24],"modality":[25],"to":[26,39],"detect":[27],"breast":[28,58,123],"tumors.":[29],"However,":[30],"accurately":[31],"delineating":[32],"tumor":[34,60,125],"region":[35],"remains":[36],"challenging":[37],"due":[38],"tumor's":[41],"size,":[42],"shape,":[43],"and":[44,53,88,99,118],"low-constraining":[45],"nature":[46],"ultrasounds.":[48],"This":[49],"study":[50],"systematically":[51],"evaluates":[52],"compares":[54],"performance":[56,67],"segmentation":[61,66],"in":[62,121],"ultrasound":[63],"images.":[64],"The":[65,77],"these":[69],"models":[70],"evaluated":[72],"across":[73],"various":[74],"loss":[75,105,119],"functions.":[76],"experimental":[78],"results":[79,111],"describe":[80],"that":[81],"residual":[83],"UNet":[84,87],"consistently":[85],"outperforms":[86],"attention":[89],"UNet.":[90],"It":[91],"achieves":[92],"highest":[94],"Dice":[95],"Coefficient":[96],"0.8238":[98],"IOU":[100],"0.6918":[102],"Tversky":[104],"(<tex":[106],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[107],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\alpha=0.4,":[108],"\\beta=0.6$</tex>).":[109],"These":[110],"highlight":[112],"synergistic":[114],"effect":[115],"architecture":[117],"function":[120],"enhancing":[122],"segmentation.":[126]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-01-21T00:00:00"}
