{"id":"https://openalex.org/W2756209008","doi":"https://doi.org/10.1109/icip.2017.8296579","title":"Mass segmentation in mammograms: A cross-sensor comparison of deep and tailored features","display_name":"Mass segmentation in mammograms: A cross-sensor comparison of deep and tailored features","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2756209008","doi":"https://doi.org/10.1109/icip.2017.8296579","mag":"2756209008"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296579","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296579","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5013827007","display_name":"Jaime S. Cardoso","orcid":"https://orcid.org/0000-0002-3760-2473"},"institutions":[{"id":"https://openalex.org/I182534213","display_name":"Universidade do Porto","ror":"https://ror.org/043pwc612","country_code":"PT","type":"education","lineage":["https://openalex.org/I182534213"]},{"id":"https://openalex.org/I4210166615","display_name":"INESC TEC","ror":"https://ror.org/05fa8ka61","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210125590","https://openalex.org/I4210166615"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Jaime S. Cardoso","raw_affiliation_strings":["INESC TEC and University of Porto, Porto, Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"INESC TEC and University of Porto, Porto, Portugal","institution_ids":["https://openalex.org/I4210166615","https://openalex.org/I182534213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027232669","display_name":"Nuno Castro Marques","orcid":"https://orcid.org/0000-0001-8250-6002"},"institutions":[{"id":"https://openalex.org/I182534213","display_name":"Universidade do Porto","ror":"https://ror.org/043pwc612","country_code":"PT","type":"education","lineage":["https://openalex.org/I182534213"]},{"id":"https://openalex.org/I4210166615","display_name":"INESC TEC","ror":"https://ror.org/05fa8ka61","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210125590","https://openalex.org/I4210166615"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Nuno Marques","raw_affiliation_strings":["INESC TEC and University of Porto, Porto, Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"INESC TEC and University of Porto, Porto, Portugal","institution_ids":["https://openalex.org/I4210166615","https://openalex.org/I182534213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067912169","display_name":"Neeraj Dhungel","orcid":"https://orcid.org/0000-0001-9048-2397"},"institutions":[{"id":"https://openalex.org/I141945490","display_name":"University of British Columbia","ror":"https://ror.org/03rmrcq20","country_code":"CA","type":"education","lineage":["https://openalex.org/I141945490"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Neeraj Dhungel","raw_affiliation_strings":["ECE, University of British Columbia, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ECE, University of British Columbia, Canada","institution_ids":["https://openalex.org/I141945490"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029215323","display_name":"Gustavo Carneiro","orcid":"https://orcid.org/0000-0002-5571-6220"},"institutions":[{"id":"https://openalex.org/I5681781","display_name":"The University of Adelaide","ror":"https://ror.org/00892tw58","country_code":"AU","type":"education","lineage":["https://openalex.org/I5681781"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"G. Carneiro","raw_affiliation_strings":["ACVT, University of Adelaide, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ACVT, University of Adelaide, Australia","institution_ids":["https://openalex.org/I5681781"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042053820","display_name":"Andrew P. Bradley","orcid":"https://orcid.org/0000-0003-0109-6844"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"A. P. Bradley","raw_affiliation_strings":["ITEE, University of Queensland, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ITEE, University of Queensland, Australia","institution_ids":["https://openalex.org/I165143802"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1737","last_page":"1741"},"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9972000122070312,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9965000152587891,"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":0.8246657848358154},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7338798642158508},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5527646541595459},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4881628155708313},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46850162744522095},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4651782214641571},{"id":"https://openalex.org/keywords/cad","display_name":"CAD","score":0.46466147899627686},{"id":"https://openalex.org/keywords/assertion","display_name":"Assertion","score":0.4531940221786499},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.449402779340744},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4278201460838318},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4187161922454834},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41417625546455383},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3326569199562073}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8246657848358154},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7338798642158508},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5527646541595459},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4881628155708313},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46850162744522095},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4651782214641571},{"id":"https://openalex.org/C194789388","wikidata":"https://www.wikidata.org/wiki/Q17855283","display_name":"CAD","level":2,"score":0.46466147899627686},{"id":"https://openalex.org/C40422974","wikidata":"https://www.wikidata.org/wiki/Q741248","display_name":"Assertion","level":2,"score":0.4531940221786499},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.449402779340744},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4278201460838318},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4187161922454834},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41417625546455383},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3326569199562073},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C199639397","wikidata":"https://www.wikidata.org/wiki/Q1788588","display_name":"Engineering drawing","level":1,"score":0.0},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icip.2017.8296579","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296579","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:digital.library.adelaide.edu.au:2440/112018","is_oa":false,"landing_page_url":"http://hdl.handle.net/2440/112018","pdf_url":null,"source":{"id":"https://openalex.org/S4306401835","display_name":"Adelaide Research & Scholarship (AR&S) (University of Adelaide)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I5681781","host_organization_name":"The University of Adelaide","host_organization_lineage":["https://openalex.org/I5681781"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8267582","raw_type":"Conference paper"},{"id":"pmh:oai:espace.library.uq.edu.au:UQ:9f68404","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402388","display_name":"Queensland's institutional digital repository (The University of Queensland)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I165143802","host_organization_name":"The University of Queensland","host_organization_lineage":["https://openalex.org/I165143802"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6600000262260437}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W177004468","https://openalex.org/W304373761","https://openalex.org/W1497499643","https://openalex.org/W1546431092","https://openalex.org/W2005089986","https://openalex.org/W2031188071","https://openalex.org/W2049633694","https://openalex.org/W2055260435","https://openalex.org/W2100495367","https://openalex.org/W2105842272","https://openalex.org/W2112270781","https://openalex.org/W2116288467","https://openalex.org/W2131807858","https://openalex.org/W2143516773","https://openalex.org/W2163605009","https://openalex.org/W2167219413","https://openalex.org/W2294923432","https://openalex.org/W6607184829","https://openalex.org/W6632752005","https://openalex.org/W6675783020","https://openalex.org/W6677084094","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W1498103021","https://openalex.org/W4230849338","https://openalex.org/W4295166216","https://openalex.org/W2177044681","https://openalex.org/W1968067090","https://openalex.org/W2345942070","https://openalex.org/W2141398161","https://openalex.org/W2016410697","https://openalex.org/W39611005","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Through":[0],"the":[1,13,34,38,51,79,85,99,104,128,144,170,173,177,189],"years,":[2],"several":[3],"CAD":[4,25],"systems":[5,64],"have":[6],"been":[7,43],"developed":[8],"to":[9,75,124],"help":[10],"radiologists":[11],"in":[12,21,33,46,57,61,81,84,108,152],"hard":[14],"task":[15],"of":[16,19,98,127,143],"detecting":[17],"signs":[18],"cancer":[20],"mammograms.":[22],"In":[23,37,88],"these":[24],"systems,":[26],"mass":[27,40,100],"segmentation":[28,41,101],"plays":[29],"a":[30,47,95,115,125,136,140,163],"central":[31],"role":[32],"decision":[35],"process.":[36],"literature,":[39],"has":[42],"typically":[44],"evaluated":[45,56,183],"intra-sensor":[48],"scenario,":[49],"where":[50],"methodology":[52],"is":[53,92],"designed":[54],"and":[55,65,71,106,135,155],"similar":[58],"data.":[59],"However,":[60],"practice,":[62],"acquisition":[63,193],"PACS":[66],"from":[67,176,187],"multiple":[68],"vendors":[69],"abound":[70],"current":[72],"works":[73],"fails":[74],"take":[76],"into":[77],"account":[78],"differences":[80],"mammogram":[82],"data":[83,185],"performance":[86],"evaluation.":[87,165],"this":[89,119],"work":[90,120],"it":[91],"argued":[93],"that":[94,172],"comprehensive":[96],"assessment":[97],"methods":[102,175],"requires":[103],"design":[105],"evaluation":[107,174],"datasets":[109],"with":[110,147],"different":[111],"properties.":[112],"To":[113],"provide":[114],"more":[116],"realistic":[117],"evaluation,":[118],"proposes:":[121],"a)":[122],"improvements":[123],"state":[126],"art":[129],"method":[130],"based":[131,151],"on":[132,158,184],"tailored":[133],"features":[134],"graph":[137],"model;":[138],"b)":[139],"head-to-head":[141],"comparison":[142],"improved":[145],"model":[146],"recently":[148],"proposed":[149],"methodologies":[150],"deep":[153],"learning":[154],"structured":[156],"prediction":[157],"four":[159],"reference":[160],"databases,":[161],"performing":[162],"cross-sensor":[164],"The":[166],"results":[167],"obtained":[168],"support":[169],"assertion":[171],"literature":[178],"are":[179],"optimistically":[180],"biased":[181],"when":[182],"gathered":[186],"exactly":[188],"same":[190],"sensor":[191],"and/or":[192],"protocol.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
