{"id":"https://openalex.org/W3004622131","doi":"https://doi.org/10.1109/bibm47256.2019.8983316","title":"Dense Encoder-Decoder Network based on Two-Level Context Enhanced Residual Attention Mechanism for Segmentation of Breast Tumors in Magnetic Resonance Imaging","display_name":"Dense Encoder-Decoder Network based on Two-Level Context Enhanced Residual Attention Mechanism for Segmentation of Breast Tumors in Magnetic Resonance Imaging","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3004622131","doi":"https://doi.org/10.1109/bibm47256.2019.8983316","mag":"3004622131"},"language":"en","primary_location":{"id":"doi:10.1109/bibm47256.2019.8983316","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm47256.2019.8983316","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/A5101828088","display_name":"Ying Gao","orcid":"https://orcid.org/0000-0002-8925-8192"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ying Gao","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology,Guangzhou,China","School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103207595","display_name":"Yin Zhao","orcid":"https://orcid.org/0009-0001-7535-3033"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yin Zhao","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology,Guangzhou,China","School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043033440","display_name":"Xiongwen Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiongwen Luo","raw_affiliation_strings":["School of Computer Science and Engineering, South China University of Technology,Guangzhou,China","School of Computer Science and Engineering, South China University of Technology, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology,Guangzhou,China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"School of Computer Science and Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007941489","display_name":"Xiping Hu","orcid":"https://orcid.org/0000-0002-4952-699X"},"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":"Xiping Hu","raw_affiliation_strings":["Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences,Shenzhen,China","Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences,Shenzhen,China","institution_ids":["https://openalex.org/I4210145761"]},{"raw_affiliation_string":"Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China","institution_ids":["https://openalex.org/I4210145761"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100984336","display_name":"Changhong Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145693","display_name":"Guangdong Academy of Medical Sciences","ror":"https://ror.org/0432p8t34","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210145693"]},{"id":"https://openalex.org/I4210153930","display_name":"Guangdong Provincial People's Hospital","ror":"https://ror.org/045kpgw45","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210153930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changhong Liang","raw_affiliation_strings":["Guangdong Academy of Medical Sciences,Guangdong Provincial People&#x0027;s Hospital,Guangzhou,China","Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Academy of Medical Sciences,Guangdong Provincial People&#x0027;s Hospital,Guangzhou,China","institution_ids":["https://openalex.org/I4210145693"]},{"raw_affiliation_string":"Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China","institution_ids":["https://openalex.org/I4210145693","https://openalex.org/I4210153930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101828088"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":0.7001,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.78980056,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1123","last_page":"1129"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9987000226974487,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9987000226974487,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.754219651222229},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.7283618450164795},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.7060514688491821},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6429836750030518},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6304207444190979},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.6004317998886108},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5757979154586792},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5415009260177612},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4990506172180176},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4645516574382782},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4623964726924896},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33016467094421387},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3245723247528076},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2171805500984192},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12446939945220947}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.754219651222229},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.7283618450164795},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7060514688491821},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6429836750030518},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6304207444190979},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6004317998886108},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5757979154586792},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5415009260177612},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4990506172180176},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4645516574382782},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4623964726924896},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33016467094421387},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3245723247528076},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2171805500984192},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12446939945220947},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm47256.2019.8983316","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm47256.2019.8983316","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":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.8199999928474426}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1903029394","https://openalex.org/W1963515430","https://openalex.org/W2194775991","https://openalex.org/W2201179457","https://openalex.org/W2235523093","https://openalex.org/W2559597482","https://openalex.org/W2560023338","https://openalex.org/W2563705555","https://openalex.org/W2771861342","https://openalex.org/W2772436090","https://openalex.org/W2798122215","https://openalex.org/W2799213142","https://openalex.org/W2799597343","https://openalex.org/W2914821433","https://openalex.org/W2921406441","https://openalex.org/W2962914239","https://openalex.org/W2963446712","https://openalex.org/W2963495494","https://openalex.org/W3105636206","https://openalex.org/W4300092737"],"related_works":["https://openalex.org/W2368824897","https://openalex.org/W1508050556","https://openalex.org/W1910862367","https://openalex.org/W2379365082","https://openalex.org/W2370747590","https://openalex.org/W2030109976","https://openalex.org/W2369260257","https://openalex.org/W2129146436","https://openalex.org/W2389120450","https://openalex.org/W55249799"],"abstract_inverted_index":{"Aiming":[0],"to":[1,43,58,81,119,124,150],"effective":[2],"early":[3],"detection":[4],"of":[5,64,78,138],"breast":[6,13,140],"cancer,":[7],"automatic":[8],"tumor":[9],"segmentation":[10,128],"based":[11,32],"on":[12,33],"Magnetic":[14],"Resonance":[15],"Imaging":[16],"(MRI)":[17],"is":[18,73,98,117,148],"concentrated":[19],"by":[20],"more":[21,23],"and":[22,60,87,123],"researchers.":[24],"This":[25],"paper":[26],"proposes":[27],"a":[28,68,83,108],"dense":[29,56,69],"encoder-decoder":[30],"network":[31],"two-level":[34,51],"context":[35],"enhanced":[36],"residual":[37,52,94],"attention":[38,53,95],"mechanism":[39],"(TLCRAM-DED).":[40],"With":[41],"respect":[42],"TLCRAM-DED,":[44],"we":[45],"design":[46],"the":[47,62,76,79,89,102,113,121,127,135],"encoding":[48],"structure":[49,54,96],"combining":[50],"with":[55,112],"block":[57],"extract":[59],"refine":[61],"features":[63,122],"different":[65],"layers.":[66],"Meanwhile,":[67],"multi-scale":[70],"atrous":[71],"convolution":[72],"used":[74,100],"at":[75],"end":[77],"encoder":[80,114],"obtain":[82],"larger":[84],"receptive":[85],"field":[86],"enrich":[88],"extracted":[90],"semantic":[91],"information.":[92],"Moreover,":[93],"(RAS)":[97],"also":[99],"for":[101],"refinement":[103],"during":[104],"decoding":[105],"stage,":[106],"while":[107],"long":[109],"connection":[110],"formed":[111],"RAS":[115],"output":[116],"applied":[118],"supplement":[120],"gradually":[125],"recover":[126],"details.":[129],"We":[130],"validated":[131],"prosed":[132],"model":[133],"in":[134],"DCE":[136],"sequence":[137],"challenging":[139],"cancer":[141],"MRI":[142],"dataset.":[143],"The":[144],"average":[145],"Dice":[146],"coefficient":[147],"up":[149],"81.04%,":[151],"which":[152],"outperforms":[153],"compared":[154],"state-of-the-arts.":[155]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
