{"id":"https://openalex.org/W3110693864","doi":"https://doi.org/10.1109/access.2020.3042889","title":"Multi-Tasking U-Shaped Network for Benign and Malignant Classification of Breast Masses","display_name":"Multi-Tasking U-Shaped Network for Benign and Malignant Classification of Breast Masses","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3110693864","doi":"https://doi.org/10.1109/access.2020.3042889","mag":"3110693864"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3042889","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3042889","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09284440.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09284440.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012971104","display_name":"Haichao Cao","orcid":"https://orcid.org/0000-0001-8910-740X"},"institutions":[{"id":"https://openalex.org/I4401727007","display_name":"Hikvision (China)","ror":"https://ror.org/02jzypx27","country_code":null,"type":"company","lineage":["https://openalex.org/I4401727007"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haichao Cao","raw_affiliation_strings":["Hangzhou Hikvision Digital Technology Company Ltd., Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Hangzhou Hikvision Digital Technology Company Ltd., Hangzhou, China","institution_ids":["https://openalex.org/I4401727007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085955762","display_name":"Shiliang Pu","orcid":"https://orcid.org/0000-0001-5269-7821"},"institutions":[{"id":"https://openalex.org/I4401727007","display_name":"Hikvision (China)","ror":"https://ror.org/02jzypx27","country_code":null,"type":"company","lineage":["https://openalex.org/I4401727007"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiliang Pu","raw_affiliation_strings":["Hangzhou Hikvision Digital Technology Company Ltd., Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Hangzhou Hikvision Digital Technology Company Ltd., Hangzhou, China","institution_ids":["https://openalex.org/I4401727007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031951156","display_name":"Wenming Tan","orcid":"https://orcid.org/0000-0003-1338-4536"},"institutions":[{"id":"https://openalex.org/I4401727007","display_name":"Hikvision (China)","ror":"https://ror.org/02jzypx27","country_code":null,"type":"company","lineage":["https://openalex.org/I4401727007"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenming Tan","raw_affiliation_strings":["Hangzhou Hikvision Digital Technology Company Ltd., Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Hangzhou Hikvision Digital Technology Company Ltd., Hangzhou, China","institution_ids":["https://openalex.org/I4401727007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029753460","display_name":"Junyan Tong","orcid":null},"institutions":[{"id":"https://openalex.org/I4401727007","display_name":"Hikvision (China)","ror":"https://ror.org/02jzypx27","country_code":null,"type":"company","lineage":["https://openalex.org/I4401727007"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junyan Tong","raw_affiliation_strings":["Hangzhou Hikvision Digital Technology Company Ltd., Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Hangzhou Hikvision Digital Technology Company Ltd., Hangzhou, China","institution_ids":["https://openalex.org/I4401727007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100366372","display_name":"Di Zhang","orcid":"https://orcid.org/0000-0001-8098-7690"},"institutions":[{"id":"https://openalex.org/I4401727007","display_name":"Hikvision (China)","ror":"https://ror.org/02jzypx27","country_code":null,"type":"company","lineage":["https://openalex.org/I4401727007"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Zhang","raw_affiliation_strings":["Hangzhou Hikvision Digital Technology Company Ltd., Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Hangzhou Hikvision Digital Technology Company Ltd., Hangzhou, China","institution_ids":["https://openalex.org/I4401727007"]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5012971104"],"corresponding_institution_ids":["https://openalex.org/I4401727007"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.2234,"has_fulltext":true,"cited_by_count":14,"citation_normalized_percentile":{"value":0.84624079,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":"8","issue":null,"first_page":"223396","last_page":"223404"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":1.0,"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":1.0,"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":0.9908999800682068,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7524970769882202},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6553941965103149},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.6508806347846985},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6450452208518982},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5786079168319702},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.47282537817955017},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.46567460894584656},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.4558615982532501},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4540567696094513},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.29871225357055664},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20254746079444885},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.11070507764816284}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7524970769882202},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6553941965103149},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.6508806347846985},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6450452208518982},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5786079168319702},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.47282537817955017},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.46567460894584656},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.4558615982532501},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4540567696094513},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.29871225357055664},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20254746079444885},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.11070507764816284},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3042889","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3042889","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09284440.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:f79a049044064d019f070a0ddf239688","is_oa":true,"landing_page_url":"https://doaj.org/article/f79a049044064d019f070a0ddf239688","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 223396-223404 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3042889","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3042889","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09284440.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.41999998688697815}],"awards":[{"id":"https://openalex.org/G2875032178","display_name":null,"funder_award_id":"2020TQ0086","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G6699828440","display_name":null,"funder_award_id":"2020T","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3110693864.pdf","grobid_xml":"https://content.openalex.org/works/W3110693864.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W304373761","https://openalex.org/W1871050032","https://openalex.org/W1901129140","https://openalex.org/W2001412060","https://openalex.org/W2043103956","https://openalex.org/W2050883594","https://openalex.org/W2060884061","https://openalex.org/W2107411682","https://openalex.org/W2109597745","https://openalex.org/W2129353515","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2199497824","https://openalex.org/W2219446152","https://openalex.org/W2280342795","https://openalex.org/W2284539364","https://openalex.org/W2299565249","https://openalex.org/W2300767860","https://openalex.org/W2493683088","https://openalex.org/W2527654160","https://openalex.org/W2560617289","https://openalex.org/W2592929672","https://openalex.org/W2592950347","https://openalex.org/W2600409369","https://openalex.org/W2619676011","https://openalex.org/W2734402721","https://openalex.org/W2751658105","https://openalex.org/W2759356748","https://openalex.org/W2787553551","https://openalex.org/W2791020862","https://openalex.org/W2793701907","https://openalex.org/W2799996975","https://openalex.org/W2864627177","https://openalex.org/W2889646458","https://openalex.org/W2899844231","https://openalex.org/W2901264604","https://openalex.org/W2919115771","https://openalex.org/W2921877691","https://openalex.org/W2964208078","https://openalex.org/W2993077515","https://openalex.org/W3021530737","https://openalex.org/W3101755009","https://openalex.org/W4254187342","https://openalex.org/W6734285614","https://openalex.org/W6743791534","https://openalex.org/W6750789872"],"related_works":["https://openalex.org/W1978572805","https://openalex.org/W2383807498","https://openalex.org/W1997992934","https://openalex.org/W1987225439","https://openalex.org/W2591697403","https://openalex.org/W4238188170","https://openalex.org/W2944728705","https://openalex.org/W2904022177","https://openalex.org/W2125114371","https://openalex.org/W2019977573"],"abstract_inverted_index":{"The":[0,140],"benign":[1],"and":[2,23,42,47,111,154,165,170,179,183],"malignant":[3],"(BM)":[4],"classification":[5,64,90],"of":[6,19,32,44,53,99,105,120,132,142,152],"breast":[7,21,45,100],"masses":[8,46,52],"based":[9],"on":[10,148],"mammography":[11],"is":[12,58,146],"a":[13,62,77,195],"key":[14,85],"step":[15],"in":[16,39],"the":[17,29,37,48,54,88,97,103,106,118,130,143,149,157,160,174,177,190],"diagnosis":[18],"early":[20],"cancer":[22],"an":[24],"effective":[25],"way":[26],"to":[27,36,60,96],"improve":[28],"survival":[30],"rate":[31],"patients.":[33],"Nevertheless,":[34],"due":[35],"differences":[38],"size,":[40],"shape":[41],"texture":[43],"visual":[49],"similarity":[50],"between":[51],"same":[55],"category,":[56],"it":[57],"difficult":[59],"obtain":[61,194],"robust":[63],"model":[65],"using":[66],"conventional":[67],"deep":[68],"learning":[69],"methods.":[70],"To":[71],"address":[72],"this":[73],"problem,":[74],"we":[75],"proposed":[76,107,144,191],"Multi-Tasking":[78],"U-shaped":[79,89],"Network":[80],"(MT-UNet),":[81],"which":[82],"contains":[83],"three":[84],"ideas:":[86],"1)":[87],"architecture":[91],"constructed":[92],"can":[93,116,128,193],"well":[94],"adapt":[95],"heterogeneity":[98],"masses;":[101],"2)":[102],"combination":[104],"truncated":[108],"normalization":[109],"method":[110,115,127,192],"adaptive":[112],"histogram":[113],"equalization":[114],"enhance":[117],"contrast":[119],"image;":[121],"3)":[122],"training":[123,138],"with":[124],"label":[125],"smoothing":[126],"alleviate":[129],"problem":[131],"convergence":[133],"difficulty":[134],"caused":[135],"by":[136],"insufficient":[137],"data.":[139],"performance":[141],"scheme":[145],"evaluated":[147],"public":[150],"dataset":[151],"DDSM":[153,158],"INbreast.":[155],"On":[156,173],"dataset,":[159,176],"Area":[161],"Under":[162],"Curve":[163],"(AUC)":[164],"accuracy":[166],"(ACC)":[167],"reached":[168,181],"0.9963":[169],"0.9817,":[171],"respectively.":[172,185],"INbreast":[175],"AUC":[178],"ACC":[180],"0.9767":[182],"0.9391,":[184],"Experimental":[186],"results":[187],"show":[188],"that":[189],"competitive":[196],"performance.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}