{"id":"https://openalex.org/W4363647715","doi":"https://doi.org/10.1117/12.2654020","title":"End-to-end brain tumor detection using a graph-feature-based classifier","display_name":"End-to-end brain tumor detection using a graph-feature-based classifier","publication_year":2023,"publication_date":"2023-04-10","ids":{"openalex":"https://openalex.org/W4363647715","doi":"https://doi.org/10.1117/12.2654020"},"language":"en","primary_location":{"id":"doi:10.1117/12.2654020","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2654020","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2023: Biomedical Applications in Molecular, Structural, and Functional Imaging","raw_type":"proceedings-article"},"type":"conference-abstract","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/A5058982778","display_name":"Mingzhe Hu","orcid":"https://orcid.org/0000-0001-9808-4967"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mingzhe Hu","raw_affiliation_strings":["Emory Univ. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100378659","display_name":"Jing Wang","orcid":"https://orcid.org/0000-0003-1618-2016"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jing Wang","raw_affiliation_strings":["Winship Cancer Institute, Emory Univ. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Winship Cancer Institute, Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081954437","display_name":"Chih\u2010Wei Chang","orcid":"https://orcid.org/0000-0002-3818-4381"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chih-Wei Chang","raw_affiliation_strings":["Winship Cancer Institute, Emory Univ. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Winship Cancer Institute, Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100365641","display_name":"Tian Liu","orcid":"https://orcid.org/0000-0001-8944-6305"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tian Liu","raw_affiliation_strings":["Winship Cancer Institute, Emory Univ. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Winship Cancer Institute, Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100619090","display_name":"Xiaofeng Yang","orcid":"https://orcid.org/0000-0001-9023-5855"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaofeng Yang","raw_affiliation_strings":["Emory Univ. (United States)","Winship Cancer Institute, Emory Univ. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]},{"raw_affiliation_string":"Winship Cancer Institute, Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150468666"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"47","last_page":"47"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9898999929428101,"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":0.9891999959945679,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6893746852874756},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6148326992988586},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.5453069806098938},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5264832973480225},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.47630298137664795},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4697414040565491},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4359467923641205},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.41558173298835754},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.41176119446754456},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.401553750038147},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.3688802719116211},{"id":"https://openalex.org/keywords/medical-physics","display_name":"Medical physics","score":0.3481149673461914},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.3241846263408661}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6893746852874756},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6148326992988586},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.5453069806098938},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5264832973480225},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.47630298137664795},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4697414040565491},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4359467923641205},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.41558173298835754},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.41176119446754456},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.401553750038147},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3688802719116211},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.3481149673461914},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.3241846263408661},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2654020","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2654020","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2023: Biomedical Applications in Molecular, Structural, and Functional Imaging","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W4379801084","https://openalex.org/W3024479225"],"abstract_inverted_index":{"Brain":[0],"tumors":[1,21,61],"are":[2,109,160],"caused":[3],"by":[4,96],"abnormal":[5],"cell":[6],"growth":[7],"and":[8,12,43,57,78,99,165,173,176],"can":[9],"cause":[10],"pain":[11],"reduced":[13],"survival":[14],"rates.":[15],"The":[16,72,156],"early":[17],"detection":[18],"of":[19,50,69,84,94,105,118,139,154],"brain":[20,40,60,146,178],"is":[22,75,135],"pivotal":[23],"in":[24,36,122],"improving":[25],"outcomes.":[26],"Recently,":[27,86],"magnetic":[28],"resonance":[29],"imaging":[30,52],"(MRI)":[31],"has":[32,89,125],"been":[33,128],"widely":[34],"deployed":[35],"clinics":[37],"to":[38,171],"diagnose":[39,59,175],"lesions":[41],"non-invasively":[42],"prevent":[44],"patients":[45],"from":[46],"receiving":[47],"radiation":[48,123,169],"doses":[49],"diagnostic":[51],"modalities.":[53],"Traditionally,":[54],"medical":[55],"oncologists":[56,170],"radiologists":[58],"as":[62],"benign":[63],"or":[64,113],"malignant":[65],"using":[66,140],"visual":[67],"analysis":[68],"MRI":[70],"images.":[71],"decision-making":[73],"process":[74],"labor":[76],"intensive,":[77],"relies":[79],"on":[80],"the":[81,92,103,116,131,136],"expertise":[82],"level":[83],"physicians.":[85],"deep":[87],"learning":[88],"dramatically":[90],"changed":[91],"landscape":[93],"oncology":[95,124],"enabling":[97],"automatic":[98],"accurate":[100],"diagnosis.":[101],"While":[102],"backbones":[104],"most":[106],"state-of-the-art":[107],"architectures":[108],"convolutional":[110],"neural":[111,120],"networks":[112,121],"vision":[114],"transformers,":[115],"application":[117],"graph":[119],"not":[126],"yet":[127],"explored.":[129],"To":[130],"authors'":[132],"knowledge,":[133],"this":[134],"first":[137],"demonstration":[138],"fully-automated":[141],"graph-feature-based":[142,158],"classifiers":[143,159],"for":[144,162],"end-to-end":[145],"tumor":[147],"detection,":[148],"indicating":[149],"an":[150],"overall":[151],"classification":[152],"accuracy":[153],"94.89%.":[155],"proposed":[157],"accessible":[161],"clinical":[163],"implementation":[164],"could":[166],"potentially":[167],"assist":[168],"precisely":[172],"accurately":[174],"prognosticate":[177],"lesions.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
