{"id":"https://openalex.org/W1519122895","doi":"https://doi.org/10.1109/isbi.2015.7163815","title":"Region segmentation in histopathological breast cancer images using deep convolutional neural network","display_name":"Region segmentation in histopathological breast cancer images using deep convolutional neural network","publication_year":2015,"publication_date":"2015-04-01","ids":{"openalex":"https://openalex.org/W1519122895","doi":"https://doi.org/10.1109/isbi.2015.7163815","mag":"1519122895"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2015.7163815","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2015.7163815","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)","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/A5108436833","display_name":"Hai Su","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hai Su","raw_affiliation_strings":["J. Crayton Pruitt Family Dept. of Biomedical Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"J. Crayton Pruitt Family Dept. of Biomedical Engineering","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100641990","display_name":"Fujun Liu","orcid":"https://orcid.org/0000-0002-1461-3567"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]},{"id":"https://openalex.org/I94062374","display_name":"Florida College","ror":"https://ror.org/010bgev76","country_code":"US","type":"education","lineage":["https://openalex.org/I94062374"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fujun Liu","raw_affiliation_strings":["Dept. of Electrical and Computer Engineering, University of Florida, FL, USA","Dept. of Electrical and Computer Engineering, University of Florida, 32601, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electrical and Computer Engineering, University of Florida, FL, USA","institution_ids":["https://openalex.org/I94062374","https://openalex.org/I33213144"]},{"raw_affiliation_string":"Dept. of Electrical and Computer Engineering, University of Florida, 32601, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108557537","display_name":"Yuanpu Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuanpu Xie","raw_affiliation_strings":["J. Crayton Pruitt Family Dept. of Biomedical Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"J. Crayton Pruitt Family Dept. of Biomedical Engineering","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076917512","display_name":"Fuyong Xing","orcid":"https://orcid.org/0000-0003-0982-8675"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]},{"id":"https://openalex.org/I94062374","display_name":"Florida College","ror":"https://ror.org/010bgev76","country_code":"US","type":"education","lineage":["https://openalex.org/I94062374"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fuyong Xing","raw_affiliation_strings":["Dept. of Electrical and Computer Engineering, University of Florida, FL, USA","Dept. of Electrical and Computer Engineering, University of Florida, 32601, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electrical and Computer Engineering, University of Florida, FL, USA","institution_ids":["https://openalex.org/I94062374","https://openalex.org/I33213144"]},{"raw_affiliation_string":"Dept. of Electrical and Computer Engineering, University of Florida, 32601, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023184933","display_name":"Sreenivasan Meyyappan","orcid":"https://orcid.org/0000-0001-7267-5072"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sreenivasan Meyyappan","raw_affiliation_strings":["J. Crayton Pruitt Family Dept. of Biomedical Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"J. Crayton Pruitt Family Dept. of Biomedical Engineering","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101725246","display_name":"Lin Yang","orcid":"https://orcid.org/0000-0002-1778-2059"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin Yang","raw_affiliation_strings":["J. Crayton Pruitt Family Dept. of Biomedical Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"J. Crayton Pruitt Family Dept. of Biomedical Engineering","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.6842,"has_fulltext":false,"cited_by_count":100,"citation_normalized_percentile":{"value":0.98184868,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"55","last_page":"58"},"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":0.9980999827384949,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9970999956130981,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8353383541107178},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8265912532806396},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7564873695373535},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7039039731025696},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6937479972839355},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6765865087509155},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5924416184425354},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5584003329277039},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5515484809875488},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.47957414388656616},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4642159938812256},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4406070113182068},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.439799040555954},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.07103055715560913}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8353383541107178},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8265912532806396},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7564873695373535},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7039039731025696},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6937479972839355},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6765865087509155},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5924416184425354},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5584003329277039},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5515484809875488},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.47957414388656616},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4642159938812256},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4406070113182068},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.439799040555954},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.07103055715560913},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2015.7163815","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2015.7163815","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5799999833106995,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1665214252","https://openalex.org/W1948745668","https://openalex.org/W2036924016","https://openalex.org/W2092985495","https://openalex.org/W2101675659","https://openalex.org/W2102605133","https://openalex.org/W2115891208","https://openalex.org/W2123269393","https://openalex.org/W2123767822","https://openalex.org/W2145287260","https://openalex.org/W2146071495","https://openalex.org/W2147796535","https://openalex.org/W2163605009","https://openalex.org/W2912728463","https://openalex.org/W6637242042","https://openalex.org/W6640764873","https://openalex.org/W6675026286","https://openalex.org/W6678394851","https://openalex.org/W6681272269","https://openalex.org/W6684191040","https://openalex.org/W6759001517"],"related_works":["https://openalex.org/W3135697610","https://openalex.org/W4375867731","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2171299904","https://openalex.org/W1647606319","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983"],"abstract_inverted_index":{"Computer":[0],"aided":[1],"diagnosis":[2],"of":[3,12,35],"breast":[4,20],"cancers":[5],"often":[6,58],"relies":[7],"on":[8],"automatic":[9,16],"image":[10,51,105],"analysis":[11],"histopathology":[13],"images.":[14],"The":[15,80,111],"region":[17,78],"segmentation":[18],"in":[19,86],"cancer":[21],"is":[22,43,57],"challenging":[23],"due":[24],"to:":[25],"i)":[26],"large":[27],"regional":[28],"variations,":[29],"and":[30,53,124],"ii)":[31],"high":[32],"computational":[33],"costs":[34],"pixel-wise":[36,77,126],"segmentation.":[37,79],"Deep":[38],"convolutional":[39,72],"neural":[40,73],"network":[41,74],"(CNN)":[42],"proven":[44],"to":[45,66,76,102],"be":[46],"an":[47,104],"effective":[48],"method":[49],"for":[50],"recognition":[52],"classification.":[54],"However,":[55],"it":[56,97],"computationally":[59],"expensive.":[60],"In":[61,94],"this":[62],"paper,":[63],"we":[64],"propose":[65],"apply":[67],"a":[68],"fast":[69],"scanning":[70],"deep":[71],"(fCNN)":[75],"fCNN":[81],"removes":[82],"the":[83,87,116,121],"redundant":[84],"computations":[85],"original":[88],"CNN":[89],"without":[90],"sacrificing":[91],"its":[92],"performance.":[93],"our":[95],"experiment":[96],"takes":[98],"only":[99],"2.3":[100],"seconds":[101],"segment":[103],"with":[106],"size":[107],"1000":[108],"\u00d7":[109],"1000.":[110],"comparison":[112],"experiments":[113],"show":[114],"that":[115],"proposed":[117],"system":[118],"outperforms":[119],"both":[120],"LBP":[122],"feature-based":[123],"texton-based":[125],"methods.":[127]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":14},{"year":2019,"cited_by_count":15},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":11},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
