{"id":"https://openalex.org/W2970949185","doi":"https://doi.org/10.1109/icip.2019.8803077","title":"3D Deep Attention Network for Survival Prediction from Magnetic Resonance Images in Glioblastoma","display_name":"3D Deep Attention Network for Survival Prediction from Magnetic Resonance Images in Glioblastoma","publication_year":2019,"publication_date":"2019-08-26","ids":{"openalex":"https://openalex.org/W2970949185","doi":"https://doi.org/10.1109/icip.2019.8803077","mag":"2970949185"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2019.8803077","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803077","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 Image Processing (ICIP)","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/A5062307188","display_name":"Zijia Liu","orcid":"https://orcid.org/0000-0002-1866-4337"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zijia Liu","raw_affiliation_strings":["Shenzhen Institutes of Advanced Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Institutes of Advanced Technology, Shenzhen, China","institution_ids":["https://openalex.org/I4210145761"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101851123","display_name":"Qiuchang Sun","orcid":"https://orcid.org/0000-0002-5049-2387"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiuchang Sun","raw_affiliation_strings":["Shenzhen Institutes of Advanced Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Institutes of Advanced Technology, Shenzhen, China","institution_ids":["https://openalex.org/I4210145761"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101113810","display_name":"Hongmin Bai","orcid":"https://orcid.org/0000-0002-3866-5230"},"institutions":[{"id":"https://openalex.org/I4210099466","display_name":"General Hospital of Guangzhou Military Command","ror":"https://ror.org/00hfbva78","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210099466"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongmin Bai","raw_affiliation_strings":["Guangzhou General Hospital of Guangzhou Military Command, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangzhou General Hospital of Guangzhou Military Command, Guangzhou, China","institution_ids":["https://openalex.org/I4210099466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102025818","display_name":"Chaofeng Liang","orcid":"https://orcid.org/0000-0002-4676-5899"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210146711","display_name":"Sun Yat-sen University Cancer Center","ror":"https://ror.org/0400g8r85","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210146711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaofeng Liang","raw_affiliation_strings":["Sun Yat-sen University Cancer Center, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University Cancer Center, Guangzhou, China","institution_ids":["https://openalex.org/I157773358","https://openalex.org/I4210146711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103049106","display_name":"Yinsheng Chen","orcid":"https://orcid.org/0000-0002-5807-1886"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinsheng Chen","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100622225","display_name":"Zhicheng Li","orcid":"https://orcid.org/0000-0003-4140-0580"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi-Cheng Li","raw_affiliation_strings":["Shenzhen Institutes of Advanced Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Institutes of Advanced Technology, Shenzhen, China","institution_ids":["https://openalex.org/I4210145761"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6979,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.68241523,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1381","last_page":"1384"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T14510","display_name":"Medical Imaging and Analysis","score":0.9998000264167786,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9995999932289124,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9993000030517578,"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":0.7604451775550842},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.718848705291748},{"id":"https://openalex.org/keywords/glioblastoma","display_name":"Glioblastoma","score":0.6718194484710693},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6685174703598022},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.6200488805770874},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5374205112457275},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5350754261016846},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4764802157878876},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.46002617478370667},{"id":"https://openalex.org/keywords/network-model","display_name":"Network model","score":0.4355873167514801},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4324977993965149},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4106981158256531},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.11478579044342041},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.10243231058120728},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.09101325273513794}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7604451775550842},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.718848705291748},{"id":"https://openalex.org/C2776194525","wikidata":"https://www.wikidata.org/wiki/Q282142","display_name":"Glioblastoma","level":2,"score":0.6718194484710693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6685174703598022},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.6200488805770874},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5374205112457275},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5350754261016846},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4764802157878876},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.46002617478370667},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.4355873167514801},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4324977993965149},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4106981158256531},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.11478579044342041},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.10243231058120728},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.09101325273513794},{"id":"https://openalex.org/C502942594","wikidata":"https://www.wikidata.org/wiki/Q3421914","display_name":"Cancer research","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},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2019.8803077","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803077","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 Image Processing (ICIP)","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":17,"referenced_works":["https://openalex.org/W1580788756","https://openalex.org/W1641498739","https://openalex.org/W2108673310","https://openalex.org/W2135404870","https://openalex.org/W2358113125","https://openalex.org/W2415877456","https://openalex.org/W2571620227","https://openalex.org/W2747986904","https://openalex.org/W2751538714","https://openalex.org/W2761668583","https://openalex.org/W2767145937","https://openalex.org/W2963232127","https://openalex.org/W2963495494","https://openalex.org/W3147894994","https://openalex.org/W6716448252","https://openalex.org/W6731743345","https://openalex.org/W6743272106"],"related_works":["https://openalex.org/W2560215812","https://openalex.org/W1602805286","https://openalex.org/W4225917631","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2990636717","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Existing":[0],"deep":[1,34],"convolutional":[2,35],"neural":[3,36],"network-based":[4],"survival":[5,42,121,126],"analysis":[6],"neither":[7],"consider":[8],"the":[9,28,57,62,81,94,100,107,113],"modern":[10],"attention":[11,39,52,110],"mechanism":[12,40],"nor":[13],"use":[14],"3D":[15,33,109],"tomographic":[16],"medical":[17],"images":[18,23],"such":[19],"as":[20],"magnetic":[21],"resonance":[22],"(MRI).":[24],"This":[25],"paper":[26],"for":[27,41],"first":[29],"time":[30],"presents":[31],"a":[32],"network":[37,59,111],"using":[38,122],"prediction":[43],"from":[44],"multiparametric":[45],"MRI":[46,123],"in":[47,80,86,119],"glioblastoma":[48],"(GBM)":[49],"patients.":[50],"The":[51,72],"module":[53],"is":[54],"incorporated":[55],"into":[56],"residual":[58],"to":[60],"enhance":[61],"representation":[63],"power":[64],"of":[65,78,115],"meaningful":[66],"features":[67],"while":[68],"suppress":[69],"unimportant":[70],"ones.":[71],"proposed":[73,108],"model":[74,97,102],"achieves":[75],"an":[76,87],"C-index":[77],"0.71":[79],"training":[82],"dataset":[83],"and":[84,99],"0.68":[85],"independent":[88],"test":[89],"dataset,":[90],"which":[91],"outperforms":[92],"both":[93],"traditional":[95,125],"Cox":[96],"(0.60,0.54)":[98],"non-attentive":[101],"(0.63,0.61).":[103],"It":[104],"indicates":[105],"that":[106],"has":[112],"potential":[114],"offering":[116],"better":[117],"performance":[118],"predicting":[120],"than":[124],"analysis.":[127]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}