{"id":"https://openalex.org/W2938476923","doi":"https://doi.org/10.1109/icassp.2019.8682502","title":"Automatic Segmentation of Nuclei in Histopathology Images Using Encoding-decoding Convolutional Neural Networks","display_name":"Automatic Segmentation of Nuclei in Histopathology Images Using Encoding-decoding Convolutional Neural Networks","publication_year":2019,"publication_date":"2019-04-17","ids":{"openalex":"https://openalex.org/W2938476923","doi":"https://doi.org/10.1109/icassp.2019.8682502","mag":"2938476923"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2019.8682502","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8682502","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://infoscience.epfl.ch/handle/20.500.14299/159582","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071233023","display_name":"Deniz Sayin Mercadier","orcid":null},"institutions":[{"id":"https://openalex.org/I201799495","display_name":"Middle East Technical University","ror":"https://ror.org/014weej12","country_code":"TR","type":"education","lineage":["https://openalex.org/I201799495"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Deniz Sayin Mercadier","raw_affiliation_strings":["Department of Computer Engineering, Middle East Technical University (METU)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Middle East Technical University (METU)","institution_ids":["https://openalex.org/I201799495"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027933458","display_name":"Beril Be\u015fb\u0131nar","orcid":null},"institutions":[{"id":"https://openalex.org/I4210121626","display_name":"Signal Processing (United States)","ror":"https://ror.org/021gzyw51","country_code":"US","type":"company","lineage":["https://openalex.org/I4210121626"]},{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH","US"],"is_corresponding":false,"raw_author_name":"Beril Besbinar","raw_affiliation_strings":["Signal Processing Laboratory (LTS4), \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Signal Processing Laboratory (LTS4), \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL)","institution_ids":["https://openalex.org/I5124864","https://openalex.org/I4210121626"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000947076","display_name":"Pascal Frossard","orcid":"https://orcid.org/0000-0002-4010-714X"},"institutions":[{"id":"https://openalex.org/I4210121626","display_name":"Signal Processing (United States)","ror":"https://ror.org/021gzyw51","country_code":"US","type":"company","lineage":["https://openalex.org/I4210121626"]},{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH","US"],"is_corresponding":false,"raw_author_name":"Pascal Frossard","raw_affiliation_strings":["Signal Processing Laboratory (LTS4), \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Signal Processing Laboratory (LTS4), \u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne (EPFL)","institution_ids":["https://openalex.org/I5124864","https://openalex.org/I4210121626"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2892,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.65138022,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"100","issue":null,"first_page":"1020","last_page":"1024"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9998999834060669,"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":0.9998999834060669,"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/T12874","display_name":"Digital Imaging for Blood Diseases","score":0.9897000193595886,"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"}},{"id":"https://openalex.org/T10146","display_name":"Cervical Cancer and HPV Research","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/computer-science","display_name":"Computer science","score":0.8487337231636047},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8156729340553284},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7657128572463989},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7205266952514648},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.6463108658790588},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5546068549156189},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.5481699705123901},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5158211588859558},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.49839091300964355},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4807322025299072},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32845181226730347},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.15321308374404907}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8487337231636047},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8156729340553284},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7657128572463989},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7205266952514648},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6463108658790588},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5546068549156189},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.5481699705123901},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5158211588859558},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.49839091300964355},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4807322025299072},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32845181226730347},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.15321308374404907},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icassp.2019.8682502","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2019.8682502","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:infoscience.epfl.ch:268681","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/159582","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"conference proceedings"},{"id":"pmh:oai:open.metu.edu.tr:11511/62802","is_oa":true,"landing_page_url":"https://hdl.handle.net/11511/62802","pdf_url":null,"source":{"id":"https://openalex.org/S4306402495","display_name":"OpenMETU (Middle East Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I201799495","host_organization_name":"Middle East Technical University","host_organization_lineage":["https://openalex.org/I201799495"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":{"id":"pmh:oai:infoscience.epfl.ch:268681","is_oa":true,"landing_page_url":"https://infoscience.epfl.ch/handle/20.500.14299/159582","pdf_url":null,"source":{"id":"https://openalex.org/S4306400487","display_name":"Infoscience (Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"conference proceedings"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W173931755","https://openalex.org/W1901129140","https://openalex.org/W1970120446","https://openalex.org/W2051765910","https://openalex.org/W2142332605","https://openalex.org/W2175543269","https://openalex.org/W2280351290","https://openalex.org/W2312404985","https://openalex.org/W2504150216","https://openalex.org/W2548342201","https://openalex.org/W2592905743","https://openalex.org/W2693096534","https://openalex.org/W2885343725","https://openalex.org/W3209544266","https://openalex.org/W6639824700","https://openalex.org/W6753285113","https://openalex.org/W6803239612"],"related_works":["https://openalex.org/W2118717649","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/W2389120450","https://openalex.org/W55249799"],"abstract_inverted_index":{"Accurate":[0],"and":[1,18,39,60,83,129,176],"fast":[2,175],"segmentation":[3,69,88,115],"of":[4,36,81,150,156,160],"nuclei":[5,52,114,151],"in":[6,13,34,63],"histopathological":[7],"images":[8],"plays":[9],"a":[10,99,111,126,138,174],"crucial":[11],"role":[12],"cancer":[14],"research":[15],"for":[16,51,142],"detection":[17],"grading,":[19],"as":[20,22],"well":[21],"personal":[23],"treatment.":[24],"Despite":[25],"the":[26,154,170],"important":[27,181],"efforts,":[28],"current":[29],"algorithms":[30],"are":[31],"still":[32],"suboptimal":[33],"terms":[35],"speed,":[37],"adaptivity":[38],"generalizability.":[40],"Popular":[41],"Deep":[42],"Convolutional":[43],"Neural":[44],"Networks":[45],"(DCNNs)":[46],"have":[47],"recently":[48],"been":[49],"utilized":[50],"segmentation,":[53],"outperforming":[54],"traditional":[55,93],"approaches":[56,96],"that":[57,77],"exploit":[58],"color":[59],"texture":[61],"features":[62],"combination":[64],"with":[65,183],"shallow":[66],"classifiers":[67],"or":[68,94,163],"algorithms.":[70],"However,":[71],"DCNNs":[72,119],"need":[73],"large":[74],"annotated":[75],"datasets":[76],"require":[78,98],"extensive":[79],"amount":[80],"time":[82],"expert":[84],"knowledge.":[85],"In":[86,106],"addition,":[87],"results":[89],"obtained":[90],"by":[91],"either":[92],"DCNN":[95],"often":[97],"post-processing":[100,164],"step":[101,165],"to":[102,144,148,152,173,185],"separate":[103],"cluttered":[104],"nuclei.":[105],"this":[107],"paper,":[108],"we":[109],"propose":[110],"computationally":[112],"efficient":[113],"framework":[116],"based":[117],"on":[118,169],"exhibiting":[120],"an":[121,131],"encoding-decoding":[122],"structure.":[123],"We":[124,135],"use":[125,137],"partially-annotated":[127],"dataset":[128],"develop":[130],"effective":[132],"training":[133],"solution.":[134],"also":[136],"weighted":[139],"background":[140],"model":[141],"network":[143],"give":[145],"more":[146],"importance":[147],"borders":[149],"overcome":[153],"problem":[155],"clutters.":[157],"The":[158],"abolition":[159],"any":[161,167],"pre-processing":[162],"without":[166],"compromise":[168],"performance":[171],"leads":[172],"parameter-free":[177],"system,":[178],"which":[179],"presents":[180],"advantages":[182],"respect":[184],"state-of-the-art.":[186]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}