{"id":"https://openalex.org/W2535146497","doi":"https://doi.org/10.1109/ipas.2014.7043316","title":"Segmentation and 3D reconstruction of MRI images for breast cancer detection","display_name":"Segmentation and 3D reconstruction of MRI images for breast cancer detection","publication_year":2014,"publication_date":"2014-11-01","ids":{"openalex":"https://openalex.org/W2535146497","doi":"https://doi.org/10.1109/ipas.2014.7043316","mag":"2535146497"},"language":"en","primary_location":{"id":"doi:10.1109/ipas.2014.7043316","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipas.2014.7043316","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Image Processing, Applications and Systems Conference","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/A5010742244","display_name":"Christo Gnonnou","orcid":null},"institutions":[{"id":"https://openalex.org/I68916915","display_name":"University of Gab\u00e8s","ror":"https://ror.org/022efad20","country_code":"TN","type":"education","lineage":["https://openalex.org/I68916915"]}],"countries":["TN"],"is_corresponding":true,"raw_author_name":"Christo Gnonnou","raw_affiliation_strings":["1Higher Institute of Computer Science and Multimedia of Gabes, Tunisia"],"affiliations":[{"raw_affiliation_string":"1Higher Institute of Computer Science and Multimedia of Gabes, Tunisia","institution_ids":["https://openalex.org/I68916915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024973351","display_name":"Nadia Smaoui","orcid":null},"institutions":[{"id":"https://openalex.org/I4210131288","display_name":"National Engineering School of Tunis","ror":"https://ror.org/03b1zjt31","country_code":"TN","type":"education","lineage":["https://openalex.org/I4210131288","https://openalex.org/I63596082"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Nadia Smaoui","raw_affiliation_strings":["Control and Energy Management Laboratory, National School of Engineers of Sfax, Tunisia"],"affiliations":[{"raw_affiliation_string":"Control and Energy Management Laboratory, National School of Engineers of Sfax, Tunisia","institution_ids":["https://openalex.org/I4210131288"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5010742244"],"corresponding_institution_ids":["https://openalex.org/I68916915"],"apc_list":null,"apc_paid":null,"fwci":2.2146,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.89429908,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9970999956130981,"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/T11361","display_name":"Digital Radiography and Breast Imaging","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/breast-cancer","display_name":"Breast cancer","score":0.608510434627533},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5562974214553833},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5419330596923828},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5320457220077515},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5133844614028931},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4717061221599579},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.44490155577659607},{"id":"https://openalex.org/keywords/cancer-detection","display_name":"Cancer detection","score":0.42080157995224},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.3673252463340759},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.32702553272247314},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.29639068245887756},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.10423770546913147}],"concepts":[{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.608510434627533},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5562974214553833},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5419330596923828},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5320457220077515},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5133844614028931},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4717061221599579},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.44490155577659607},{"id":"https://openalex.org/C2985322473","wikidata":"https://www.wikidata.org/wiki/Q3044843","display_name":"Cancer detection","level":3,"score":0.42080157995224},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.3673252463340759},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.32702553272247314},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.29639068245887756},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.10423770546913147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ipas.2014.7043316","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipas.2014.7043316","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Image Processing, Applications and Systems Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.7200000286102295,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W27461462","https://openalex.org/W1498299056","https://openalex.org/W1676195771","https://openalex.org/W1974452559","https://openalex.org/W1986579304","https://openalex.org/W2045127019","https://openalex.org/W2057424904","https://openalex.org/W2057722565","https://openalex.org/W2065789139","https://openalex.org/W2096526848","https://openalex.org/W2104353968","https://openalex.org/W2106787323","https://openalex.org/W2120091091","https://openalex.org/W2146692942","https://openalex.org/W2184231612","https://openalex.org/W2229412420","https://openalex.org/W2240902024","https://openalex.org/W3127529150","https://openalex.org/W4245611435"],"related_works":["https://openalex.org/W1669643531","https://openalex.org/W2122581818","https://openalex.org/W1631910785","https://openalex.org/W2159066190","https://openalex.org/W2739874619","https://openalex.org/W2110230079","https://openalex.org/W2117933325","https://openalex.org/W2117664411","https://openalex.org/W1721780360","https://openalex.org/W1507266234"],"abstract_inverted_index":{"Cancer":[0],"is":[1,14,54,184,204],"a":[2,80,100,123,134,143,160,217],"dense":[3],"and":[4,66,79,97,142,158,197,216],"abnormal":[5],"cells":[6],"proliferation":[7],"in":[8,18,42,58],"the":[9,15,27,51,71,108,116,139,148,152,179,182,195,201,213,222],"body":[10],"tissue.":[11],"Breast":[12],"cancer":[13,78,89],"most":[16],"common":[17],"woman's":[19],"life.":[20],"Fortunately,":[21],"science":[22],"evolution":[23],"has":[24],"led":[25],"to":[26,38,106,121,137,146,168,173],"development":[28],"of":[29,60,73,77,84,118,166,181],"medical":[30],"imaging":[31],"techniques.":[32],"The":[33,127],"latter":[34],"are":[35,131],"efficiently":[36],"used":[37,128],"detect":[39],"any":[40],"abnormality":[41],"breast":[43,88,140,153,174],"parenchyma.":[44],"Among":[45],"these":[46],"techniques,":[47],"we":[48,155],"can":[49],"mention":[50],"MRI":[52,85,95],"which":[53,171],"very":[55],"relevant":[56],"especially":[57],"terms":[59],"dubious":[61],"image":[62],"analysis":[63],"by":[64,186,207],"mammography":[65],"ultrasound.":[67],"Our":[68],"research":[69,169],"addresses":[70],"problem":[72],"detecting":[74],"this":[75,177],"type":[76],"three":[81],"dimensional":[82],"reconstruction":[83,203],"images":[86,96,167],"for":[87],"detection.":[90],"We":[91,110],"have":[92,111,156],"segmented":[93,125],"2D":[94],"then":[98,205],"make":[99],"3D":[101,202],"reconstruction.":[102],"Segmentation":[103],"allows":[104],"us":[105],"locate":[107],"tumor.":[109,149],"looked":[112],"much":[113],"more":[114],"towards":[115],"elimination":[117],"false":[119],"positives":[120],"obtain":[122],"clear":[124],"image.":[126],"segmentation":[129,180],"methods":[130],"based":[132],"on":[133],"structural":[135],"approach":[136,145],"isolate":[138],"edge":[141],"region":[144],"extract":[147],"For":[150],"segmenting":[151],"skinline,":[154],"developed":[157],"proposed":[159],"method":[161],"that":[162],"browses":[163],"all":[164],"pixels":[165],"those":[170],"belong":[172],"edge.":[175],"After":[176],"extraction,":[178],"tumor":[183,196],"performed":[185,206],"K-means":[187],"algorithm":[188],"preceded":[189],"filtering":[190],"operations.":[191],"To":[192],"better":[193],"visualize":[194],"understand":[198],"its":[199],"expansion,":[200],"an":[208],"indirect":[209],"volume":[210,219],"rendering":[211,220],"method,":[212,221],"Marching":[214],"Cubes":[215],"direct":[218],"Maximum":[223],"Intensity":[224],"Projection.":[225]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":2}],"updated_date":"2026-02-01T03:34:12.195049","created_date":"2025-10-10T00:00:00"}
