{"id":"https://openalex.org/W2918658282","doi":"https://doi.org/10.1117/12.2511750","title":"Using transfer learning for a deep learning model observer","display_name":"Using transfer learning for a deep learning model observer","publication_year":2019,"publication_date":"2019-03-04","ids":{"openalex":"https://openalex.org/W2918658282","doi":"https://doi.org/10.1117/12.2511750","mag":"2918658282"},"language":"en","primary_location":{"id":"doi:10.1117/12.2511750","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2511750","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment","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/A5111065082","display_name":"William Murphy","orcid":null},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"William Murphy","raw_affiliation_strings":["Univ. of Surrey (United Kingdom)"],"affiliations":[{"raw_affiliation_string":"Univ. of Surrey (United Kingdom)","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062698689","display_name":"Mark Halling\u2010Brown","orcid":"https://orcid.org/0000-0002-6247-4768"},"institutions":[{"id":"https://openalex.org/I2799660017","display_name":"Royal Surrey County Hospital","ror":"https://ror.org/02w7x5c08","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I2799660017","https://openalex.org/I4210146582"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mark D. Halling-Brown","raw_affiliation_strings":["Royal Surrey County Hospital (United Kingdom)"],"affiliations":[{"raw_affiliation_string":"Royal Surrey County Hospital (United Kingdom)","institution_ids":["https://openalex.org/I2799660017"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080910385","display_name":"Emma Lewis","orcid":null},"institutions":[{"id":"https://openalex.org/I2799660017","display_name":"Royal Surrey County Hospital","ror":"https://ror.org/02w7x5c08","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I2799660017","https://openalex.org/I4210146582"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Emma Lewis","raw_affiliation_strings":["Royal Surrey County Hospital (United Kingdom)"],"affiliations":[{"raw_affiliation_string":"Royal Surrey County Hospital (United Kingdom)","institution_ids":["https://openalex.org/I2799660017"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112530893","display_name":"Premkumar Elangovan","orcid":null},"institutions":[{"id":"https://openalex.org/I2799660017","display_name":"Royal Surrey County Hospital","ror":"https://ror.org/02w7x5c08","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I2799660017","https://openalex.org/I4210146582"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Premkumar Elangovan","raw_affiliation_strings":["Royal Surrey County Hospital (United Kingdom)"],"affiliations":[{"raw_affiliation_string":"Royal Surrey County Hospital (United Kingdom)","institution_ids":["https://openalex.org/I2799660017"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007219692","display_name":"Kenneth C. Young","orcid":"https://orcid.org/0000-0003-3491-257X"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]},{"id":"https://openalex.org/I2799660017","display_name":"Royal Surrey County Hospital","ror":"https://ror.org/02w7x5c08","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I2799660017","https://openalex.org/I4210146582"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kenneth C. Young","raw_affiliation_strings":["Royal Surrey County Hospital  (United Kingdom)","Univ. of Surrey (United Kingdom)"],"affiliations":[{"raw_affiliation_string":"Royal Surrey County Hospital  (United Kingdom)","institution_ids":["https://openalex.org/I2799660017"]},{"raw_affiliation_string":"Univ. of Surrey (United Kingdom)","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106633687","display_name":"David R. Dance","orcid":null},"institutions":[{"id":"https://openalex.org/I2799660017","display_name":"Royal Surrey County Hospital","ror":"https://ror.org/02w7x5c08","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I2799660017","https://openalex.org/I4210146582"]},{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"David R. Dance","raw_affiliation_strings":["Royal Surrey County Hospital  (United Kingdom)","Univ. of Surrey (United Kingdom)"],"affiliations":[{"raw_affiliation_string":"Royal Surrey County Hospital  (United Kingdom)","institution_ids":["https://openalex.org/I2799660017"]},{"raw_affiliation_string":"Univ. of Surrey (United Kingdom)","institution_ids":["https://openalex.org/I28290843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064537633","display_name":"Kevin Wells","orcid":"https://orcid.org/0000-0002-4658-8060"},"institutions":[{"id":"https://openalex.org/I28290843","display_name":"University of Surrey","ror":"https://ror.org/00ks66431","country_code":"GB","type":"education","lineage":["https://openalex.org/I28290843"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kevin Wells","raw_affiliation_strings":["Univ. of Surrey (United Kingdom)"],"affiliations":[{"raw_affiliation_string":"Univ. of Surrey (United Kingdom)","institution_ids":["https://openalex.org/I28290843"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5111065082"],"corresponding_institution_ids":["https://openalex.org/I28290843"],"apc_list":null,"apc_paid":null,"fwci":0.42,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.6944809,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"14","issue":null,"first_page":"13","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9994999766349792,"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":0.9994999766349792,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9984999895095825,"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/computer-science","display_name":"Computer science","score":0.7310857772827148},{"id":"https://openalex.org/keywords/observer","display_name":"Observer (physics)","score":0.7236366868019104},{"id":"https://openalex.org/keywords/toolbox","display_name":"Toolbox","score":0.7116116285324097},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.706427812576294},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.680386483669281},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5376286506652832},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48269128799438477},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.467494398355484},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4512934386730194},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33192962408065796}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7310857772827148},{"id":"https://openalex.org/C2780704645","wikidata":"https://www.wikidata.org/wiki/Q9251458","display_name":"Observer (physics)","level":2,"score":0.7236366868019104},{"id":"https://openalex.org/C2777655017","wikidata":"https://www.wikidata.org/wiki/Q1501161","display_name":"Toolbox","level":2,"score":0.7116116285324097},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.706427812576294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.680386483669281},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5376286506652832},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48269128799438477},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.467494398355484},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4512934386730194},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33192962408065796},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2511750","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2511750","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment","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":17,"referenced_works":["https://openalex.org/W93817077","https://openalex.org/W1686810756","https://openalex.org/W1976435141","https://openalex.org/W2067829201","https://openalex.org/W2095554436","https://openalex.org/W2131470200","https://openalex.org/W2144551243","https://openalex.org/W2596918562","https://openalex.org/W2793088928","https://openalex.org/W2797597904","https://openalex.org/W2803450353","https://openalex.org/W3004955311","https://openalex.org/W4234482113","https://openalex.org/W6603827313","https://openalex.org/W6637373629","https://openalex.org/W6734599602","https://openalex.org/W6752005292"],"related_works":["https://openalex.org/W3192840557","https://openalex.org/W4380075502","https://openalex.org/W2889705046","https://openalex.org/W4223943233","https://openalex.org/W4360585206","https://openalex.org/W4312200629","https://openalex.org/W4382286161","https://openalex.org/W2960456850","https://openalex.org/W2946016983","https://openalex.org/W4317565044"],"abstract_inverted_index":{"Recent":[0],"developments":[1],"in":[2,12,134,154],"technology":[3],"assessment":[4,74],"and":[5,38,60,83,131,166,179,190],"optimization":[6],"methodology":[7],"have":[8,100],"seen":[9],"an":[10,21],"expansion":[11],"the":[13,28,36,44,50,65,107,148,157],"use":[14],"of":[15,40,67,94,136,150,164,169,188,193],"Virtual":[16],"Clinical":[17],"Trials":[18],"(VCT)":[19],"as":[20],"alternative":[22],"to":[23,58,116],"conventional":[24],"clinical":[25],"trials.":[26],"However,":[27],"ultimate":[29],"value":[30],"gained":[31],"from":[32,43],"VCTs":[33],"relies":[34],"on":[35,106],"speed":[37],"quality":[39],"results":[41,142],"generated":[42],"VCT":[45,159],"pipeline.":[46],"In":[47],"many":[48],"cases":[49],"end-point":[51],"human":[52],"observer":[53,70,84,104],"represents":[54],"a":[55,68,102,119,144,162,167,186,191],"bottle-neck":[56],"due":[57],"resource":[59],"time":[61],"limitations.":[62],"This":[63],"motivates":[64],"development":[66],"machine-based":[69],"for":[71,81,96,147],"key":[72],"task-based":[73],"studies.":[75],"Previous":[76],"work":[77],"using":[78,156,177],"Deep":[79],"Learning":[80,122],"detection":[82,149],"studies":[85],"has":[86,173],"shown":[87],"significant":[88],"promise,":[89],"but":[90],"requires":[91],"large":[92],"amounts":[93],"data":[95],"training.":[97],"We":[98],"therefore":[99],"built":[101],"model":[103,172],"based":[105],"VGG19":[108],"neural":[109],"network":[110],"architecture":[111],"combined":[112],"with":[113],"transfer":[114],"learning":[115],"successfully":[117],"train":[118],"TLMO":[120],"(Transfer":[121],"Model":[123],"Observer)":[124],"that":[125],"can":[126],"detect":[127],"both":[128],"screen-detected":[129,181],"malignancies":[130],"simulated":[132,151],"lesions":[133],"images":[135],"303":[137,139],"x":[138],"pixels.":[140],"Our":[141],"demonstrate":[143],"strong":[145],"response":[146],"lesions,":[152],"4mm":[153],"diameter,":[155],"OPTIMAM":[158],"Toolbox,":[160],"achieving":[161],"sensitivity":[163,187],"0.78":[165],"specificity":[168,192],"0.92.":[170],"The":[171],"also":[174],"been":[175],"tested":[176],"well-defined":[178],"ill-defined":[180],"masses":[182],"where":[183],"it":[184],"achieved":[185],"0.85":[189],"0.83.":[194]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}