{"id":"https://openalex.org/W2792506782","doi":"https://doi.org/10.1117/12.2292654","title":"Extraction of breast lesions from ultrasound imagery: Bhattacharyya gradient flow approach","display_name":"Extraction of breast lesions from ultrasound imagery: Bhattacharyya gradient flow approach","publication_year":2018,"publication_date":"2018-03-02","ids":{"openalex":"https://openalex.org/W2792506782","doi":"https://doi.org/10.1117/12.2292654","mag":"2792506782"},"language":"en","primary_location":{"id":"doi:10.1117/12.2292654","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2292654","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2018: Image Processing","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/A5081416883","display_name":"Mahsa Torkaman","orcid":"https://orcid.org/0000-0003-4022-1601"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mahsa Torkaman","raw_affiliation_strings":["Stony Brook Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Stony Brook Univ. (United States)","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070821128","display_name":"Romeil Sandhu","orcid":"https://orcid.org/0000-0002-7659-7590"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Romeil Sandhu","raw_affiliation_strings":["Stony Brook Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Stony Brook Univ. (United States)","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012935165","display_name":"Allen Tannenbaum","orcid":"https://orcid.org/0000-0002-0567-5256"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Allen Tannenbaum","raw_affiliation_strings":["Stony Brook Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Stony Brook Univ. (United States)","institution_ids":["https://openalex.org/I59553526"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5081416883"],"corresponding_institution_ids":["https://openalex.org/I59553526"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02528156,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"103","last_page":"103"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9993000030517578,"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":0.9993000030517578,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9936000108718872,"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/bhattacharyya-distance","display_name":"Bhattacharyya distance","score":0.9844399094581604},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5783225893974304},{"id":"https://openalex.org/keywords/s\u00f8rensen\u2013dice-coefficient","display_name":"S\u00f8rensen\u2013Dice coefficient","score":0.5698683261871338},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5657231211662292},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5325355529785156},{"id":"https://openalex.org/keywords/ultrasound","display_name":"Ultrasound","score":0.5293444395065308},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5125494003295898},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5005478858947754},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.4956279993057251},{"id":"https://openalex.org/keywords/breast-ultrasound","display_name":"Breast ultrasound","score":0.45505672693252563},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.4451366066932678},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.41911131143569946},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4162128269672394},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.332653284072876},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3238552212715149},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3232530355453491},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.3154611885547638},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.3031770586967468},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.2611728310585022},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.22013559937477112},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2192406952381134},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.10883378982543945},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.09230205416679382}],"concepts":[{"id":"https://openalex.org/C24145651","wikidata":"https://www.wikidata.org/wiki/Q2901249","display_name":"Bhattacharyya distance","level":2,"score":0.9844399094581604},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5783225893974304},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.5698683261871338},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5657231211662292},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5325355529785156},{"id":"https://openalex.org/C143753070","wikidata":"https://www.wikidata.org/wiki/Q162564","display_name":"Ultrasound","level":2,"score":0.5293444395065308},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5125494003295898},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5005478858947754},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.4956279993057251},{"id":"https://openalex.org/C2777423100","wikidata":"https://www.wikidata.org/wiki/Q1888238","display_name":"Breast ultrasound","level":5,"score":0.45505672693252563},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.4451366066932678},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.41911131143569946},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4162128269672394},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.332653284072876},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3238552212715149},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3232530355453491},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.3154611885547638},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.3031770586967468},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.2611728310585022},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.22013559937477112},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2192406952381134},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.10883378982543945},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.09230205416679382}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2292654","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2292654","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2018: Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8999999761581421,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1484228140","https://openalex.org/W1578285471","https://openalex.org/W1991113069","https://openalex.org/W1997678218","https://openalex.org/W2026636957","https://openalex.org/W2030594766","https://openalex.org/W2054010632","https://openalex.org/W2070744377","https://openalex.org/W2079690285","https://openalex.org/W2090550165","https://openalex.org/W2108447811","https://openalex.org/W2109294327","https://openalex.org/W2132513126","https://openalex.org/W2132984323","https://openalex.org/W2134275275","https://openalex.org/W2146033519","https://openalex.org/W2149197198","https://openalex.org/W3110683067","https://openalex.org/W4248721357","https://openalex.org/W6657375792","https://openalex.org/W6679079610","https://openalex.org/W6786768871"],"related_works":["https://openalex.org/W4387215474","https://openalex.org/W2804525729","https://openalex.org/W3037414627","https://openalex.org/W3021454079","https://openalex.org/W3164435407","https://openalex.org/W2157102420","https://openalex.org/W3088342099","https://openalex.org/W4200090100","https://openalex.org/W4387444505","https://openalex.org/W4295442860"],"abstract_inverted_index":{"Breast":[0],"cancer":[1],"is":[2,47,61,85,125],"one":[3],"of":[4,18,35,71,80,130,138,163],"the":[5,14,24,30,53,69,89,93,108,115,121,128,131,136,139,144,164],"most":[6,54,162],"commonly":[7],"diagnosed":[8],"neoplasms":[9],"among":[10,20],"American":[11],"women":[12,21],"and":[13,33,39,44,57,107,154],"second":[15,59],"leading":[16],"cause":[17],"death":[19],"all":[22],"over":[23],"world.":[25],"In":[26,64],"order":[27,50],"to":[28,51,103,149],"reduce":[29],"mortality":[31],"rate":[32],"cost":[34],"treatment,":[36],"early":[37],"diagnosis":[38,46],"treatment":[40,56],"are":[41],"essential.":[42],"Accurate":[43],"reliable":[45],"required":[48],"in":[49,161],"ensure":[52],"effective":[55],"a":[58],"opinion":[60],"often":[62],"advisable.":[63],"this":[65],"paper,":[66],"we":[67],"address":[68],"problem":[70],"breast":[72,105],"lesion":[73,109],"detection":[74],"from":[75],"ultrasound":[76,104],"imagery":[77],"by":[78,87,113],"means":[79],"active":[81],"contours,":[82],"whose":[83],"evolution":[84],"driven":[86],"maximizing":[88,114],"Bhattacharyya":[90,157],"distance<sup>1</sup>":[91],"between":[92],"probability":[94],"density":[95],"functions":[96],"(PDFs).":[97],"The":[98],"proposed":[99,140],"method":[100,141],"was":[101,111],"applied":[102],"imagery,":[106],"boundary":[110,129],"obtained":[112],"distance-based":[116],"energy":[117],"functional":[118],"such":[119],"that":[120,156],"maximum":[122],"(optimal":[123],"contour)":[124],"attained":[126],"at":[127],"potential":[132],"lesion.":[133],"We":[134],"compared":[135],"results":[137],"quantitatively":[142],"using":[143],"Dice":[145],"coefficient":[146],"(similarity":[147],"index)<sup>2</sup>":[148],"well-known":[150],"GrowCut":[151,160],"segmentation":[152],"method<sup>3</sup>":[153],"demonstrated":[155],"approach":[158],"outperforms":[159],"cases.":[165]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}