{"id":"https://openalex.org/W3005510482","doi":"https://doi.org/10.1109/bibm47256.2019.8983412","title":"Dose Prediction for Prostate Radiation Treatment: Feasibility of a Distance-Based Deep Learning Model","display_name":"Dose Prediction for Prostate Radiation Treatment: Feasibility of a Distance-Based Deep Learning Model","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3005510482","doi":"https://doi.org/10.1109/bibm47256.2019.8983412","mag":"3005510482"},"language":"en","primary_location":{"id":"doi:10.1109/bibm47256.2019.8983412","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm47256.2019.8983412","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5034580944","display_name":"Tavakoli H. Maryam","orcid":null},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tavakoli H. Maryam","raw_affiliation_strings":["University of North Carolina at Charlotte,Dept. of Software Information Systems,Charlotte,United States","Dept. of Software Information Systems, University of North Carolina at Charlotte, Charlotte, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of North Carolina at Charlotte,Dept. of Software Information Systems,Charlotte,United States","institution_ids":["https://openalex.org/I102149020"]},{"raw_affiliation_string":"Dept. of Software Information Systems, University of North Carolina at Charlotte, Charlotte, United States","institution_ids":["https://openalex.org/I102149020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068551338","display_name":"Boshu Ru","orcid":"https://orcid.org/0000-0001-9620-1306"},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Boshu Ru","raw_affiliation_strings":["University of North Carolina at Charlotte,Dept. of Software Information Systems,Charlotte,United States","Dept. of Software Information Systems, University of North Carolina at Charlotte, Charlotte, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of North Carolina at Charlotte,Dept. of Software Information Systems,Charlotte,United States","institution_ids":["https://openalex.org/I102149020"]},{"raw_affiliation_string":"Dept. of Software Information Systems, University of North Carolina at Charlotte, Charlotte, United States","institution_ids":["https://openalex.org/I102149020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066989731","display_name":"Tianyi Xie","orcid":"https://orcid.org/0009-0000-5732-7379"},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianyi Xie","raw_affiliation_strings":["University of North Carolina at Charlotte,Dept. of Software Information Systems,Charlotte,United States","Dept. of Software Information Systems, University of North Carolina at Charlotte, Charlotte, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of North Carolina at Charlotte,Dept. of Software Information Systems,Charlotte,United States","institution_ids":["https://openalex.org/I102149020"]},{"raw_affiliation_string":"Dept. of Software Information Systems, University of North Carolina at Charlotte, Charlotte, United States","institution_ids":["https://openalex.org/I102149020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026696284","display_name":"Mirsad Had\u017eikadi\u0107","orcid":"https://orcid.org/0000-0003-3235-3700"},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mirsad Hadzikadic","raw_affiliation_strings":["University of North Carolina at Charlotte,Dept. of Software Information Systems,Charlotte,United States","Dept. of Software Information Systems, University of North Carolina at Charlotte, Charlotte, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of North Carolina at Charlotte,Dept. of Software Information Systems,Charlotte,United States","institution_ids":["https://openalex.org/I102149020"]},{"raw_affiliation_string":"Dept. of Software Information Systems, University of North Carolina at Charlotte, Charlotte, United States","institution_ids":["https://openalex.org/I102149020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069570157","display_name":"Qiuwen Wu","orcid":"https://orcid.org/0000-0003-0748-7280"},"institutions":[{"id":"https://openalex.org/I4210126298","display_name":"Duke Medical Center","ror":"https://ror.org/03njmea73","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210126298","https://openalex.org/I4210144876"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Q. Jackie Wu","raw_affiliation_strings":["Duke University Medical Center,Dept. of Radiation Oncology,Durham,United States","Dept. of Radiation Oncology, Duke University Medical Center, Durham, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Duke University Medical Center,Dept. of Radiation Oncology,Durham,United States","institution_ids":["https://openalex.org/I4210126298"]},{"raw_affiliation_string":"Dept. of Radiation Oncology, Duke University Medical Center, Durham, United States","institution_ids":["https://openalex.org/I4210126298"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029749535","display_name":"Yaorong Ge","orcid":"https://orcid.org/0000-0002-9576-0293"},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yaorong Ge","raw_affiliation_strings":["University of North Carolina at Charlotte,Dept. of Software Information Systems,Charlotte,United States","Dept. of Software Information Systems, University of North Carolina at Charlotte, Charlotte, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of North Carolina at Charlotte,Dept. of Software Information Systems,Charlotte,United States","institution_ids":["https://openalex.org/I102149020"]},{"raw_affiliation_string":"Dept. of Software Information Systems, University of North Carolina at Charlotte, Charlotte, United States","institution_ids":["https://openalex.org/I102149020"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.1901,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.80341746,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"2379","last_page":"2386"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10358","display_name":"Advanced Radiotherapy Techniques","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10358","display_name":"Advanced Radiotherapy Techniques","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/3108","display_name":"Radiation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9975000023841858,"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"}},{"id":"https://openalex.org/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9947999715805054,"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/voxel","display_name":"Voxel","score":0.7792034149169922},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7388549447059631},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.689755380153656},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6533249616622925},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6010724902153015},{"id":"https://openalex.org/keywords/radiation-treatment-planning","display_name":"Radiation treatment planning","score":0.5540364384651184},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.513443112373352},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.47602468729019165},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.46814921498298645},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4337603449821472},{"id":"https://openalex.org/keywords/distance-transform","display_name":"Distance transform","score":0.42889341711997986},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.4191874563694},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4024730920791626},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3444161117076874},{"id":"https://openalex.org/keywords/radiation-therapy","display_name":"Radiation therapy","score":0.29000967741012573},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1488085389137268},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14426204562187195},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1399177610874176},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.13801905512809753}],"concepts":[{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.7792034149169922},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7388549447059631},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.689755380153656},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6533249616622925},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6010724902153015},{"id":"https://openalex.org/C201645570","wikidata":"https://www.wikidata.org/wiki/Q830637","display_name":"Radiation treatment planning","level":3,"score":0.5540364384651184},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.513443112373352},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.47602468729019165},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.46814921498298645},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4337603449821472},{"id":"https://openalex.org/C73621898","wikidata":"https://www.wikidata.org/wiki/Q2940504","display_name":"Distance transform","level":3,"score":0.42889341711997986},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.4191874563694},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4024730920791626},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3444161117076874},{"id":"https://openalex.org/C509974204","wikidata":"https://www.wikidata.org/wiki/Q180507","display_name":"Radiation therapy","level":2,"score":0.29000967741012573},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1488085389137268},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14426204562187195},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1399177610874176},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.13801905512809753},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm47256.2019.8983412","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm47256.2019.8983412","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.5}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1810897226","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1963932209","https://openalex.org/W1978752707","https://openalex.org/W2029328961","https://openalex.org/W2033456044","https://openalex.org/W2069905590","https://openalex.org/W2097512974","https://openalex.org/W2337438617","https://openalex.org/W2756545703","https://openalex.org/W2759710969","https://openalex.org/W2763599350","https://openalex.org/W2898197178","https://openalex.org/W2898515460","https://openalex.org/W2902472343","https://openalex.org/W2939627886","https://openalex.org/W2962835968","https://openalex.org/W2963865536","https://openalex.org/W4289752807","https://openalex.org/W6637373629","https://openalex.org/W6638566332","https://openalex.org/W6639824700","https://openalex.org/W6753426341","https://openalex.org/W6755860911"],"related_works":["https://openalex.org/W2118717649","https://openalex.org/W2413243053","https://openalex.org/W410723623","https://openalex.org/W2015341305","https://openalex.org/W2035068594","https://openalex.org/W4225593417","https://openalex.org/W2573498121","https://openalex.org/W2050534380","https://openalex.org/W2110113201","https://openalex.org/W2015086390"],"abstract_inverted_index":{"This":[0,130,222],"study":[1],"aims":[2],"to":[3,17,41,71,101,125,139,163,177,203,236],"demonstrate":[4],"the":[5,39,43,46,73,102,108,119,127,157,165,170,181,192,196,200,208,241,246,292,299],"feasibility":[6],"of":[7,13,38,45,118,173,255],"using":[8,96,264],"a":[9,19,78,188],"novel":[10],"distance-based":[11,148,247],"representation":[12,32,131,149,213,225],"3D":[14,62,174],"CT-scan":[15,63],"images":[16],"train":[18],"deep":[20,47,97,248],"learning":[21,48,98,105,249,285],"model":[22,279],"for":[23,50,111,253,303],"dose":[24,76,94,262,305],"predictions":[25],"in":[26,77,92,142,151,180,211,224],"radiation":[27,51,182],"treatment":[28,52,183],"planning.":[29,53],"The":[30,147,272],"distance":[31,167,194,218],"is":[33,137,154,161,187],"inspired":[34,155],"by":[35,156,216],"previous":[36],"knowledge":[37,159],"domain":[40,158],"increase":[42],"generalizability":[44],"models":[49,99,114,250],"Conventional":[54],"knowledge-based":[55],"planning":[56,184],"methods":[57],"extract":[58],"engineered":[59,287],"features":[60],"from":[61,195,219],"images,":[64],"as":[65,67,280,282],"well":[66,281],"other":[68,82],"patients'":[69,258],"features,":[70],"predict":[72],"best":[74],"achievable":[75],"cancerous":[79,197,220],"area":[80],"and":[81,135,145,160,199,229,232,260,268],"organs":[83],"at":[84],"risk.":[85],"Recent":[86],"studies":[87,120,179],"have":[88],"shown":[89],"higher":[90,297],"accuracy":[91],"voxel-level":[93,261],"prediction":[95,254],"compared":[100,275],"conventional":[103,283],"machine":[104,284],"approaches.":[106],"Since":[107],"data":[109],"resources":[110],"training":[112],"these":[113],"are":[115],"limited,":[116],"most":[117],"use":[121],"2D":[122,171],"contour":[123,209],"information":[124,168],"represent":[126],"patient":[128,143,237],"anatomy.":[129],"loses":[132],"volumetric":[133,166],"information,":[134],"it":[136,227],"sensitive":[138],"small":[140],"changes":[141],"orientation":[144,230],"translation.":[146],"introduced":[150],"this":[152],"paper":[153],"able":[162],"maintain":[164],"despite":[169],"slicing":[172],"CT-image.":[175],"According":[176],"prior":[178,212,300],"domain,":[185],"there":[186],"strong":[189],"association":[190],"between":[191],"organs-at-risk":[193],"volume":[198],"patient's":[201],"vulnerability":[202,259],"receive":[204],"excessive":[205],"dose.":[206],"Therefore,":[207],"value":[210],"was":[214,294],"replaced":[215],"voxel":[217],"volume.":[221],"modification":[223],"makes":[226],"transition":[228],"invariant":[231],"adds":[233],"potential":[234],"robustness":[235],"positioning":[238],"differences":[239],"during":[240],"imaging/planning":[242],"process.":[243],"We":[244,289],"evaluated":[245],"through":[251],"experiments":[252],"prostate":[256],"cancer":[257],"distribution":[263,306],"convolutional":[265],"neural":[266],"network":[267],"U-net":[269,278],"models,":[270],"respectively.":[271],"results":[273,302],"were":[274],"with":[276,286],"contour-based":[277],"representations.":[288],"found":[290],"that":[291],"performance":[293],"comparable":[295],"or":[296],"than":[298],"state-of-the-art":[301],"prostate-cancer":[304],"prediction.":[307]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
