{"id":"https://openalex.org/W2593998733","doi":"https://doi.org/10.1117/12.2253982","title":"Fine-tuning convolutional deep features for MRI based brain tumor classification","display_name":"Fine-tuning convolutional deep features for MRI based brain tumor classification","publication_year":2017,"publication_date":"2017-03-03","ids":{"openalex":"https://openalex.org/W2593998733","doi":"https://doi.org/10.1117/12.2253982","mag":"2593998733"},"language":"en","primary_location":{"id":"doi:10.1117/12.2253982","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2253982","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","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/A5011432412","display_name":"Kaoutar Ben Ahmed","orcid":"https://orcid.org/0000-0002-5269-8733"},"institutions":[{"id":"https://openalex.org/I240042149","display_name":"Abdelmalek Essa\u00e2di University","ror":"https://ror.org/03c4shz64","country_code":"MA","type":"education","lineage":["https://openalex.org/I240042149"]}],"countries":["MA"],"is_corresponding":true,"raw_author_name":"Kaoutar B. Ahmed","raw_affiliation_strings":["Abdelmalek Essaadi Univ. (Morocco)"],"affiliations":[{"raw_affiliation_string":"Abdelmalek Essaadi Univ. (Morocco)","institution_ids":["https://openalex.org/I240042149"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000168449","display_name":"Lawrence Hall","orcid":"https://orcid.org/0000-0002-7898-8456"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lawrence O. Hall","raw_affiliation_strings":["Univ. of South Florida (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of South Florida (United States)","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053211631","display_name":"Dmitry B. Goldgof","orcid":"https://orcid.org/0000-0001-5461-863X"},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dmitry B. Goldgof","raw_affiliation_strings":["Univ. of South Florida (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of South Florida (United States)","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002010460","display_name":"Renhao Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I2613432","display_name":"University of South Florida","ror":"https://ror.org/032db5x82","country_code":"US","type":"education","lineage":["https://openalex.org/I2613432"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Renhao Liu","raw_affiliation_strings":["Univ. of South Florida (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of South Florida (United States)","institution_ids":["https://openalex.org/I2613432"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032533490","display_name":"Robert A. Gatenby","orcid":"https://orcid.org/0000-0002-1621-1510"},"institutions":[{"id":"https://openalex.org/I3019308854","display_name":"Moffitt Cancer Center","ror":"https://ror.org/01xf75524","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I3019308854"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robert A. Gatenby","raw_affiliation_strings":["H. Lee Moffitt Cancer Ctr. and Research Institute (United States)"],"affiliations":[{"raw_affiliation_string":"H. Lee Moffitt Cancer Ctr. and Research Institute (United States)","institution_ids":["https://openalex.org/I3019308854"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5011432412"],"corresponding_institution_ids":["https://openalex.org/I240042149"],"apc_list":null,"apc_paid":null,"fwci":3.8678,"has_fulltext":false,"cited_by_count":76,"citation_normalized_percentile":{"value":0.93471037,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"10134","issue":null,"first_page":"101342E","last_page":"101342E"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":1.0,"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/T10862","display_name":"AI in cancer detection","score":0.9959999918937683,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9925000071525574,"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":0.8771913051605225},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.818692684173584},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7345609664916992},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6382848024368286},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.550913393497467},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5387071371078491},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5240026712417603},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5118669867515564},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.4718729853630066},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4595469832420349},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4538031220436096},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4521581530570984},{"id":"https://openalex.org/keywords/fine-tuning","display_name":"Fine-tuning","score":0.43227729201316833},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37379902601242065},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.27236536145210266}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8771913051605225},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.818692684173584},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7345609664916992},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6382848024368286},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.550913393497467},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5387071371078491},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5240026712417603},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5118669867515564},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.4718729853630066},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4595469832420349},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4538031220436096},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4521581530570984},{"id":"https://openalex.org/C157524613","wikidata":"https://www.wikidata.org/wiki/Q2828883","display_name":"Fine-tuning","level":2,"score":0.43227729201316833},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37379902601242065},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27236536145210266},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"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:10.1117/12.2253982","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2253982","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1824790222","https://openalex.org/W1849277567","https://openalex.org/W2006223989","https://openalex.org/W2037227137","https://openalex.org/W2062118960","https://openalex.org/W2077947937","https://openalex.org/W2097475056","https://openalex.org/W2101926813","https://openalex.org/W2102605133","https://openalex.org/W2103004421","https://openalex.org/W2106837051","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2128739912","https://openalex.org/W2141125852","https://openalex.org/W2148461049","https://openalex.org/W2161381512","https://openalex.org/W2163605009","https://openalex.org/W2587530497","https://openalex.org/W2953066166","https://openalex.org/W2963173190","https://openalex.org/W4237028743","https://openalex.org/W4294375521","https://openalex.org/W6639204139","https://openalex.org/W6651874931","https://openalex.org/W6675026286","https://openalex.org/W6676001293","https://openalex.org/W6676297131","https://openalex.org/W6676622225","https://openalex.org/W6682778277","https://openalex.org/W6683619738","https://openalex.org/W6684191040","https://openalex.org/W6764750447"],"related_works":["https://openalex.org/W2952813363","https://openalex.org/W4378678253","https://openalex.org/W2911497689","https://openalex.org/W4360783045","https://openalex.org/W2770149305","https://openalex.org/W2972076240","https://openalex.org/W3167930666","https://openalex.org/W3185156046","https://openalex.org/W3014952856","https://openalex.org/W2964843961"],"abstract_inverted_index":{"Prediction":[0],"of":[1,79,100,108],"survival":[2,91,142],"time":[3,20,143],"from":[4,59,83],"brain":[5],"tumor":[6],"magnetic":[7],"resonance":[8],"images":[9],"(MRI)":[10],"is":[11,117],"not":[12],"commonly":[13],"performed":[14],"and":[15,67,134],"would":[16,57],"ordinarily":[17],"be":[18,31,51],"a":[19,109,121,126,151],"consuming":[21],"process.":[22],"However,":[23],"current":[24,72],"cross-sectional":[25],"imaging":[26],"techniques,":[27],"particularly":[28],"MRI,":[29],"can":[30,49],"used":[32,52],"to":[33,53,140],"generate":[34],"many":[35],"features":[36,69,81],"that":[37],"may":[38],"provide":[39,95],"information":[40,48],"on":[41,125],"the":[42,77,98,106,136,141],"patient\u2019s":[43],"prognosis,":[44],"including":[45],"survival.":[46],"This":[47],"potentially":[50],"identify":[54],"individuals":[55],"who":[56],"benefit":[58],"more":[60],"aggressive":[61],"therapy.":[62],"Rather":[63],"than":[64],"using":[65],"pre-defined":[66],"hand-engineered":[68],"as":[70],"with":[71],"radiomics":[73],"methods,":[74],"we":[75],"investigated":[76],"use":[78],"deep":[80],"extracted":[82],"pre-trained":[84,110],"convolutional":[85],"neural":[86],"networks":[87],"(CNNs)":[88],"in":[89,104,150],"predicting":[90],"time.":[92],"We":[93,119],"also":[94],"evidence":[96],"for":[97],"power":[99],"domain":[101],"specific":[102],"fine-tuning":[103],"improving":[105],"performance":[107],"CNN\u2019s,":[111],"even":[112],"though":[113],"our":[114],"data":[115],"set":[116],"small.":[118],"fine-tuned":[120],"CNN":[122],"initially":[123],"trained":[124],"large":[127],"natural":[128],"image":[129],"recognition":[130],"dataset":[131],"(Imagenet":[132],"ILSVRC)":[133],"transferred":[135],"learned":[137],"feature":[138],"representations":[139],"prediction":[144],"task,":[145],"obtaining":[146],"over":[147],"81%":[148],"accuracy":[149],"leave":[152],"one":[153],"out":[154],"cross":[155],"validation.":[156]},"counts_by_year":[{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
