{"id":"https://openalex.org/W4410087549","doi":"https://doi.org/10.1109/tim.2025.3566814","title":"MulFF-Net: A Domain-Aware Multiscale Feature Fusion Network for Breast Ultrasound Image Segmentation With Radiomic Applications","display_name":"MulFF-Net: A Domain-Aware Multiscale Feature Fusion Network for Breast Ultrasound Image Segmentation With Radiomic Applications","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4410087549","doi":"https://doi.org/10.1109/tim.2025.3566814"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2025.3566814","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tim.2025.3566814","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/tim.2025.3566814","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111300695","display_name":"Arita Halder","orcid":null},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Arita Halder","raw_affiliation_strings":["School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, India"],"raw_orcid":"https://orcid.org/0009-0009-7194-6139","affiliations":[{"raw_affiliation_string":"School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044064329","display_name":"Manjunatha Mahadevappa","orcid":"https://orcid.org/0000-0003-4700-9080"},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Manjunatha Mahadevappa","raw_affiliation_strings":["School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, India"],"raw_orcid":"https://orcid.org/0000-0003-4700-9080","affiliations":[{"raw_affiliation_string":"School of Medical Science and Technology, Indian Institute of Technology Kharagpur, Kharagpur, India","institution_ids":["https://openalex.org/I145894827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5111300695"],"corresponding_institution_ids":["https://openalex.org/I145894827"],"apc_list":null,"apc_paid":null,"fwci":8.693,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.97202401,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"74","issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9952999949455261,"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":0.9952999949455261,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9948999881744385,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9670000076293945,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.635238528251648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6274163126945496},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5805916786193848},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5651271939277649},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5229542851448059},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5227953791618347},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.5119324922561646},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5012271404266357},{"id":"https://openalex.org/keywords/breast-ultrasound","display_name":"Breast ultrasound","score":0.4741784334182739},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4657704532146454},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.45998093485832214},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44620272517204285},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41721075773239136},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.11684978008270264},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11466208100318909},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.09727510809898376},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.09658390283584595}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.635238528251648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6274163126945496},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5805916786193848},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5651271939277649},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5229542851448059},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5227953791618347},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.5119324922561646},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5012271404266357},{"id":"https://openalex.org/C2777423100","wikidata":"https://www.wikidata.org/wiki/Q1888238","display_name":"Breast ultrasound","level":5,"score":0.4741784334182739},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4657704532146454},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.45998093485832214},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44620272517204285},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41721075773239136},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.11684978008270264},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11466208100318909},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.09727510809898376},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.09658390283584595},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","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/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2025.3566814","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tim.2025.3566814","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/tim.2025.3566814","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tim.2025.3566814","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2108598243","https://openalex.org/W2110505741","https://openalex.org/W2113282793","https://openalex.org/W2194775991","https://openalex.org/W2763355946","https://openalex.org/W2787091153","https://openalex.org/W2911840775","https://openalex.org/W2963104294","https://openalex.org/W2963163009","https://openalex.org/W2963446712","https://openalex.org/W2969908837","https://openalex.org/W2991372685","https://openalex.org/W2996290406","https://openalex.org/W3011974116","https://openalex.org/W3049209383","https://openalex.org/W3081752372","https://openalex.org/W3128646645","https://openalex.org/W3158905005","https://openalex.org/W3168491317","https://openalex.org/W3170968229","https://openalex.org/W3198147788","https://openalex.org/W3204245437","https://openalex.org/W4246193833","https://openalex.org/W4280545198","https://openalex.org/W4283700835","https://openalex.org/W4289752563","https://openalex.org/W4310595042","https://openalex.org/W4313476628","https://openalex.org/W4365801723","https://openalex.org/W4383753324","https://openalex.org/W4385237236","https://openalex.org/W4385299230","https://openalex.org/W4386858051","https://openalex.org/W4388491525","https://openalex.org/W4388937239","https://openalex.org/W4399571984","https://openalex.org/W4399939663","https://openalex.org/W4400188734","https://openalex.org/W6750469568","https://openalex.org/W6762718338"],"related_works":["https://openalex.org/W4379231730","https://openalex.org/W4389858081","https://openalex.org/W2501551404","https://openalex.org/W4298131179","https://openalex.org/W2113201962","https://openalex.org/W4385583601","https://openalex.org/W4395685956","https://openalex.org/W1522196789","https://openalex.org/W3021454079","https://openalex.org/W4393378497"],"abstract_inverted_index":{"Ultrasound":[0],"is":[1],"a":[2,41,48,66,104,155],"widely":[3],"used,":[4],"non-ionizing,":[5],"and":[6,25,91,111,135],"cost-effective":[7],"imaging":[8],"modality":[9],"for":[10,32,51,158],"breast":[11,52,129],"cancer":[12],"screening.":[13],"However,":[14],"its":[15],"inherent":[16],"limitations,":[17],"such":[18],"as":[19],"low":[20],"contrast,":[21],"variable":[22],"lesion":[23,27,145],"sizes,":[24],"indistinct":[26],"boundaries":[28],"pose":[29],"significant":[30],"challenges":[31],"precise":[33],"segmentation.":[34,55],"To":[35],"mitigate":[36],"these":[37],"issues,":[38],"we":[39],"proposed":[40],"domain-aware":[42],"Multi-Scale":[43],"Feature":[44],"Fusion":[45],"Network":[46],"(MulFF-Net),":[47],"novel":[49],"approach":[50],"ultrasound":[53,130],"image":[54],"The":[56],"fundamental":[57],"novelty":[58],"of":[59,65],"MulFF-Net":[60,102,124],"lies":[61],"in":[62,150],"the":[63,74,93,117,143],"incorporation":[64],"Dilated":[67],"Convolution":[68],"Spatial":[69],"Attention":[70],"Module":[71],"(DCSAM)":[72],"into":[73],"skip":[75,79],"connections.":[76],"Unlike":[77],"conventional":[78],"connections,":[80],"this":[81],"advanced":[82],"design":[83],"captures":[84],"multi-scale":[85],"contextual":[86],"information":[87],"with":[88,108],"spatial":[89,112],"attention":[90,113],"enhances":[92],"model\u2019s":[94],"ability":[95],"to":[96,120,139],"accurately":[97],"localize":[98],"segmentation":[99,122],"regions.":[100],"Furthermore,":[101],"utilizes":[103],"domain-specific":[105],"encoder":[106],"coupled":[107],"both":[109],"channel":[110],"mechanisms,":[114],"further":[115,159],"refining":[116],"feature":[118],"representation":[119],"improve":[121],"performance.":[123],"was":[125],"evaluated":[126],"on":[127],"three":[128],"datasets,":[131],"achieving":[132],"superior":[133],"IoU":[134],"Dice":[136],"scores":[137],"compared":[138],"state-of-the-art":[140],"models.":[141],"Additionally,":[142],"generated":[144],"masks":[146],"demonstrated":[147],"potential":[148],"utility":[149],"downstream":[151],"radiomic":[152],"analysis,":[153],"offering":[154],"valuable":[156],"tool":[157],"clinical":[160],"applications.":[161]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}