{"id":"https://openalex.org/W2535841211","doi":"https://doi.org/10.1109/embc.2016.7591628","title":"Breast lesion detection and characterization with 3D features","display_name":"Breast lesion detection and characterization with 3D features","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2535841211","doi":"https://doi.org/10.1109/embc.2016.7591628","mag":"2535841211","pmid":"https://pubmed.ncbi.nlm.nih.gov/28269184"},"language":"en","primary_location":{"id":"doi:10.1109/embc.2016.7591628","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2016.7591628","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5061528247","display_name":"Anchana Balakrishnannair Sreekumari","orcid":"https://orcid.org/0000-0002-7054-5079"},"institutions":[{"id":"https://openalex.org/I4210142581","display_name":"General Electric (India)","ror":"https://ror.org/04dd9ss52","country_code":"IN","type":"company","lineage":["https://openalex.org/I1332737386","https://openalex.org/I4210142581"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Arathi Sreekumari","raw_affiliation_strings":["GE Global Research, Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"GE Global Research, Bengaluru, India","institution_ids":["https://openalex.org/I4210142581"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008441252","display_name":"K. S. Shriram","orcid":null},"institutions":[{"id":"https://openalex.org/I4210142581","display_name":"General Electric (India)","ror":"https://ror.org/04dd9ss52","country_code":"IN","type":"company","lineage":["https://openalex.org/I1332737386","https://openalex.org/I4210142581"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"K S Shriram","raw_affiliation_strings":["GE Global Research, Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"GE Global Research, Bengaluru, India","institution_ids":["https://openalex.org/I4210142581"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112288363","display_name":"Vivek Vaidya","orcid":null},"institutions":[{"id":"https://openalex.org/I4210142581","display_name":"General Electric (India)","ror":"https://ror.org/04dd9ss52","country_code":"IN","type":"company","lineage":["https://openalex.org/I1332737386","https://openalex.org/I4210142581"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vivek Vaidya","raw_affiliation_strings":["GE Global Research, Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"GE Global Research, Bengaluru, India","institution_ids":["https://openalex.org/I4210142581"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5061528247"],"corresponding_institution_ids":["https://openalex.org/I4210142581"],"apc_list":null,"apc_paid":null,"fwci":0.857,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.84282673,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"4101","last_page":"4104"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998999834060669,"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":0.9998999834060669,"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/T10885","display_name":"Gene expression and cancer classification","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11134","display_name":"Breast Lesions and Carcinomas","score":0.9833999872207642,"subfield":{"id":"https://openalex.org/subfields/2734","display_name":"Pathology and Forensic Medicine"},"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/lesion","display_name":"Lesion","score":0.6827592253684998},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6126396656036377},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5908437371253967},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5545724630355835},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4365634024143219},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.420514315366745},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.34469133615493774},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.29596763849258423},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.20751678943634033}],"concepts":[{"id":"https://openalex.org/C2781156865","wikidata":"https://www.wikidata.org/wiki/Q827023","display_name":"Lesion","level":2,"score":0.6827592253684998},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6126396656036377},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5908437371253967},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5545724630355835},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4365634024143219},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.420514315366745},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.34469133615493774},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.29596763849258423},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.20751678943634033}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001331","descriptor_name":"Automation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001331","descriptor_name":"Automation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001331","descriptor_name":"Automation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001943","descriptor_name":"Breast Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D001943","descriptor_name":"Breast Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D001943","descriptor_name":"Breast Neoplasms","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016217","descriptor_name":"Ultrasonography, Mammary","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D016217","descriptor_name":"Ultrasonography, Mammary","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D016217","descriptor_name":"Ultrasonography, Mammary","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D055088","descriptor_name":"Early Detection of Cancer","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D055088","descriptor_name":"Early Detection of Cancer","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D055088","descriptor_name":"Early Detection of Cancer","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc.2016.7591628","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2016.7591628","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:28269184","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/28269184","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1699734612","https://openalex.org/W1989033067","https://openalex.org/W1994307947","https://openalex.org/W2028672930","https://openalex.org/W2041277244","https://openalex.org/W2060005420","https://openalex.org/W2102957917","https://openalex.org/W2119067550","https://openalex.org/W2129534965","https://openalex.org/W2142787402","https://openalex.org/W2161969291","https://openalex.org/W2163352848","https://openalex.org/W6677828672"],"related_works":["https://openalex.org/W3193043704","https://openalex.org/W4386259002","https://openalex.org/W1546989560","https://openalex.org/W3171520305","https://openalex.org/W3135126032","https://openalex.org/W1924178503","https://openalex.org/W4308716060","https://openalex.org/W4280648719","https://openalex.org/W4386937079","https://openalex.org/W2901774584"],"abstract_inverted_index":{"Automated":[0],"Breast":[1],"Ultrasound":[2],"(ABUS)":[3],"is":[4],"highly":[5],"effective":[6],"as":[7,112],"breast":[8],"cancer":[9],"screening":[10],"adjunct":[11],"technology.":[12],"Automation":[13],"can":[14],"greatly":[15],"enhance":[16],"the":[17,20,24,67,88,134],"efficiency":[18],"of":[19,26,47,58,70,122,138],"clinician":[21],"sifting":[22],"through":[23],"quantum":[25],"data":[27],"in":[28],"ABUS":[29],"volumes":[30],"to":[31,99],"spot":[32],"lesions.":[33],"We":[34,53,94],"have":[35],"implemented":[36],"a":[37,55,120],"fully":[38],"automatic":[39],"generic":[40],"algorithm":[41],"pipeline":[42],"for":[43,60,90,104,140,145],"detection":[44,72,142],"and":[45,73,143],"characterization":[46],"lesions":[48,111],"on":[49,63],"such":[50],"3D":[51],"volumes.":[52],"compare":[54],"wide":[56],"range":[57],"features":[59],"region":[61,81,102],"description":[62],"their":[64],"effectiveness":[65],"at":[66,83],"dual":[68],"goals":[69],"lesion":[71,84,92,105,141,146],"characterization.":[74,147],"On":[75],"multiple":[76],"feature":[77],"images,":[78],"we":[79,108,130],"compute":[80],"descriptors":[82,103],"candidate":[85,101],"locations":[86],"obviating":[87],"need":[89],"explicit":[91],"segmentation.":[93],"use":[95],"Random":[96],"Forests":[97],"classifier":[98],"evaluate":[100],"detection.":[106],"Further,":[107],"categorize":[109],"true":[110],"Malignant":[113],"or":[114],"other":[115],"masses":[116],"(e.g.":[117],"Cysts).":[118],"Over":[119],"database":[121],"145":[123],"volumes,":[124],"with":[125],"36":[126],"biopsy":[127],"verified":[128],"lesions,":[129],"achieved":[131],"Area":[132],"Under":[133],"Curve":[135],"(AUC)":[136],"values":[137],"92.6%":[139],"89%":[144]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
