{"id":"https://openalex.org/W2922091131","doi":"https://doi.org/10.1117/12.2512277","title":"A shell and kernel descriptor based joint deep learning model for predicting breast lesion malignancy","display_name":"A shell and kernel descriptor based joint deep learning model for predicting breast lesion malignancy","publication_year":2019,"publication_date":"2019-03-13","ids":{"openalex":"https://openalex.org/W2922091131","doi":"https://doi.org/10.1117/12.2512277","mag":"2922091131"},"language":"en","primary_location":{"id":"doi:10.1117/12.2512277","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2512277","pdf_url":null,"source":{"id":"https://openalex.org/S4306519510","display_name":"Medical Imaging 2019: Computer-Aided Diagnosis","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2019: Computer-Aided Diagnosis","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100785328","display_name":"Zhiguo Zhou","orcid":"https://orcid.org/0000-0003-4031-3178"},"institutions":[{"id":"https://openalex.org/I867280407","display_name":"The University of Texas Southwestern Medical Center","ror":"https://ror.org/05byvp690","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I867280407"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhiguo Zhou","raw_affiliation_strings":["The Univ. of Texas Southwestern Medical Ctr. at Dallas (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Univ. of Texas Southwestern Medical Ctr. at Dallas (United States)","institution_ids":["https://openalex.org/I867280407"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025079276","display_name":"Genggeng Qin","orcid":"https://orcid.org/0000-0002-7563-3924"},"institutions":[{"id":"https://openalex.org/I4210103346","display_name":"Nanfang Hospital","ror":"https://ror.org/01eq10738","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210103346"]},{"id":"https://openalex.org/I58200834","display_name":"Southern Medical University","ror":"https://ror.org/01vjw4z39","country_code":"CN","type":"education","lineage":["https://openalex.org/I58200834"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Genggeng Qin","raw_affiliation_strings":["Nanfang Hospital, Southern Medical Univ. (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanfang Hospital, Southern Medical Univ. (China)","institution_ids":["https://openalex.org/I58200834","https://openalex.org/I4210103346"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054075262","display_name":"Pingkun Yan","orcid":"https://orcid.org/0000-0002-9779-2141"},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pingkun Yan","raw_affiliation_strings":["Rensselaer Polytechnic Institute (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rensselaer Polytechnic Institute (United States)","institution_ids":["https://openalex.org/I165799507"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007226326","display_name":"Hongxia Hao","orcid":"https://orcid.org/0000-0002-2324-0803"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongxia Hao","raw_affiliation_strings":["Xidian Univ. (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian Univ. (China)","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018120191","display_name":"Steve Jiang","orcid":"https://orcid.org/0000-0002-3083-6752"},"institutions":[{"id":"https://openalex.org/I867280407","display_name":"The University of Texas Southwestern Medical Center","ror":"https://ror.org/05byvp690","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I867280407"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Steve Jiang","raw_affiliation_strings":["The Univ. of Texas Southwestern Medical Ctr. at Dallas (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Univ. of Texas Southwestern Medical Ctr. at Dallas (United States)","institution_ids":["https://openalex.org/I867280407"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100378659","display_name":"Jing Wang","orcid":"https://orcid.org/0000-0003-1618-2016"},"institutions":[{"id":"https://openalex.org/I867280407","display_name":"The University of Texas Southwestern Medical Center","ror":"https://ror.org/05byvp690","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I867280407"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jing Wang","raw_affiliation_strings":["The Univ. of Texas Southwestern Medical Ctr. at Dallas (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Univ. of Texas Southwestern Medical Ctr. at Dallas (United States)","institution_ids":["https://openalex.org/I867280407"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"100","last_page":"100"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9983000159263611,"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/T10885","display_name":"Gene expression and cancer classification","score":0.993399977684021,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6581531763076782},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6335955858230591},{"id":"https://openalex.org/keywords/malignancy","display_name":"Malignancy","score":0.6276987195014954},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5958800315856934},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.5181823372840881},{"id":"https://openalex.org/keywords/shell","display_name":"Shell (structure)","score":0.48418405652046204},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4801346957683563},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40462738275527954},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.23267292976379395},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11884459853172302},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.11839544773101807},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11308249831199646}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6581531763076782},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6335955858230591},{"id":"https://openalex.org/C2779399171","wikidata":"https://www.wikidata.org/wiki/Q1483951","display_name":"Malignancy","level":2,"score":0.6276987195014954},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5958800315856934},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.5181823372840881},{"id":"https://openalex.org/C2781052500","wikidata":"https://www.wikidata.org/wiki/Q2230313","display_name":"Shell (structure)","level":2,"score":0.48418405652046204},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4801346957683563},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40462738275527954},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.23267292976379395},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11884459853172302},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.11839544773101807},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11308249831199646},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2512277","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2512277","pdf_url":null,"source":{"id":"https://openalex.org/S4306519510","display_name":"Medical Imaging 2019: Computer-Aided Diagnosis","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2019: Computer-Aided Diagnosis","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.5699999928474426}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1488083143","https://openalex.org/W1997410071","https://openalex.org/W1998926479","https://openalex.org/W2007752234","https://openalex.org/W2049337423","https://openalex.org/W2144647583","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2280192650","https://openalex.org/W2612594530","https://openalex.org/W2760915313","https://openalex.org/W2766676715","https://openalex.org/W4207058970","https://openalex.org/W6628990388","https://openalex.org/W6687483927","https://openalex.org/W6745342844"],"related_works":["https://openalex.org/W2092561569","https://openalex.org/W2377100155","https://openalex.org/W4375867731","https://openalex.org/W2793887421","https://openalex.org/W4389671191","https://openalex.org/W3153228984","https://openalex.org/W4247453431","https://openalex.org/W4312779314","https://openalex.org/W1965152511","https://openalex.org/W2032491827"],"abstract_inverted_index":{"Predicting":[0],"lesion":[1,76],"malignancy":[2,58,77],"accurately":[3],"and":[4,19,25,45,66,91,120,125,138,151,158,166,196,205],"reliably":[5],"in":[6,36,57,71,79],"digital":[7],"breast":[8,14,75],"tomosynthesis":[9],"is":[10,84,99],"critically":[11],"important":[12,34,55,203],"for":[13,74,86],"cancer":[15],"screening.":[16],"Tumor":[17],"shape":[18,90],"interactive":[20],"effect":[21],"between":[22],"the":[23,32,40,43,50,62,81,88,96,103,114,148,178,188,193,201,206,211],"tumor":[24,51,89,105],"surrounding":[26,92],"normal":[27,93],"tissue":[28,94],"are":[29],"two":[30],"of":[31,47],"most":[33,202],"indicators":[35],"radiologists\u2019":[37],"reading.":[38],"On":[39],"other":[41],"hand,":[42],"density":[44],"texture":[46],"region":[48],"within":[49],"also":[52],"play":[53],"an":[54],"role":[56],"classification.":[59],"Inspired":[60],"by":[61],"above":[63],"observations,":[64],"shell":[65,82,124,157,185,195],"kernel":[67,97,159,197],"descriptors":[68,198],"were":[69,144,170],"proposed":[70],"this":[72,162],"work":[73],"prediction,":[78],"which":[80],"descriptor":[83,98,180],"used":[85,100,145,171],"describing":[87],"while":[95],"to":[101,118,128,146],"describe":[102],"internal":[104],"region.":[106],"A":[107],"joint":[108],"deep":[109],"learning":[110],"model":[111,150,209],"based":[112,181],"on":[113],"AlexNet":[115],"was":[116],"designed":[117],"learn":[119],"fuse":[121],"features":[122,204],"from":[123,155],"kernel.":[126],"Additionally,":[127],"obtain":[129],"more":[130],"reliable":[131,140],"predictive":[132,149,208],"results,":[133],"a":[134,139],"multi-objective":[135],"optimization":[136],"algorithm":[137],"classifier":[141],"fusion":[142],"strategy":[143],"train":[147],"optimally":[152],"combine":[153],"outputs":[154],"both":[156],"descriptors.":[160],"In":[161],"study,":[163],"278":[164],"malignant":[165],"685":[167],"benign":[168],"cases":[169],"through":[172],"2-fold":[173],"cross":[174],"validation.":[175],"Compared":[176],"with":[177],"single":[179],"models":[182],"using":[183],"either":[184],"or":[186],"kernel,":[187],"experimental":[189],"results":[190],"demonstrated":[191],"that":[192],"combined":[194],"can":[199],"capture":[200],"corresponding":[207],"achieved":[210],"best":[212],"performance":[213],"as":[214],"well.":[215]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
