{"id":"https://openalex.org/W2559338397","doi":"https://doi.org/10.1109/iceee.2016.7751192","title":"Thresholding methods review for microcalcifications segmentation on mammography images in obvious, subtle, and cluster categories","display_name":"Thresholding methods review for microcalcifications segmentation on mammography images in obvious, subtle, and cluster categories","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2559338397","doi":"https://doi.org/10.1109/iceee.2016.7751192","mag":"2559338397"},"language":"en","primary_location":{"id":"doi:10.1109/iceee.2016.7751192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iceee.2016.7751192","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 13th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)","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/A5022792736","display_name":"Jonathan Hern\u00e1ndez-Capistr\u00e1n","orcid":"https://orcid.org/0000-0002-4689-5343"},"institutions":[{"id":"https://openalex.org/I39824353","display_name":"National Institute of Astrophysics, Optics and Electronics","ror":"https://ror.org/00bpmmc63","country_code":"MX","type":"facility","lineage":["https://openalex.org/I39824353"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Jonathan Hernandez-Capistran","raw_affiliation_strings":["Electronics Department National Institute of Astrophysics, Optics, and Electronics, M\u00e9xico, Puebla"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics Department National Institute of Astrophysics, Optics, and Electronics, M\u00e9xico, Puebla","institution_ids":["https://openalex.org/I39824353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010976827","display_name":"Jorge Mart\u00ednez\u2010Carballido","orcid":null},"institutions":[{"id":"https://openalex.org/I39824353","display_name":"National Institute of Astrophysics, Optics and Electronics","ror":"https://ror.org/00bpmmc63","country_code":"MX","type":"facility","lineage":["https://openalex.org/I39824353"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Jorge F. Martinez-Carballido","raw_affiliation_strings":["Electronics Department National Institute of Astrophysics, Optics, and Electronics, M\u00e9xico, Puebla"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronics Department National Institute of Astrophysics, Optics, and Electronics, M\u00e9xico, Puebla","institution_ids":["https://openalex.org/I39824353"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I39824353"],"apc_list":null,"apc_paid":null,"fwci":0.1941,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.51690452,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"13","issue":null,"first_page":"1","last_page":"6"},"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":0.9987999796867371,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9951000213623047,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7435176968574524},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.739368200302124},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7258875966072083},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6761239171028137},{"id":"https://openalex.org/keywords/mammography","display_name":"Mammography","score":0.6691125631332397},{"id":"https://openalex.org/keywords/microcalcification","display_name":"Microcalcification","score":0.6489840149879456},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5700420141220093},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5671581029891968},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5573399662971497},{"id":"https://openalex.org/keywords/digital-mammography","display_name":"Digital mammography","score":0.5249911546707153},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5198257565498352},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.47249093651771545},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.17176687717437744},{"id":"https://openalex.org/keywords/breast-cancer","display_name":"Breast cancer","score":0.1430523693561554}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7435176968574524},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.739368200302124},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7258875966072083},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6761239171028137},{"id":"https://openalex.org/C2780472235","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Mammography","level":4,"score":0.6691125631332397},{"id":"https://openalex.org/C2781129008","wikidata":"https://www.wikidata.org/wiki/Q1933877","display_name":"Microcalcification","level":5,"score":0.6489840149879456},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5700420141220093},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5671581029891968},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5573399662971497},{"id":"https://openalex.org/C2781281974","wikidata":"https://www.wikidata.org/wiki/Q324634","display_name":"Digital mammography","level":5,"score":0.5249911546707153},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5198257565498352},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.47249093651771545},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.17176687717437744},{"id":"https://openalex.org/C530470458","wikidata":"https://www.wikidata.org/wiki/Q128581","display_name":"Breast cancer","level":3,"score":0.1430523693561554},{"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/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iceee.2016.7751192","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iceee.2016.7751192","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 13th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W304373761","https://openalex.org/W1978818813","https://openalex.org/W1980171109","https://openalex.org/W1982054279","https://openalex.org/W1996930148","https://openalex.org/W2027091505","https://openalex.org/W2070680736","https://openalex.org/W2083970667","https://openalex.org/W2085476449","https://openalex.org/W2089748508","https://openalex.org/W2090550165","https://openalex.org/W2109283698","https://openalex.org/W2111383637","https://openalex.org/W2133003941","https://openalex.org/W2133059825","https://openalex.org/W2148518080","https://openalex.org/W2172359919","https://openalex.org/W4245100975"],"related_works":["https://openalex.org/W2378946663","https://openalex.org/W2122667464","https://openalex.org/W2031284012","https://openalex.org/W2054831422","https://openalex.org/W2106731176","https://openalex.org/W2354834859","https://openalex.org/W2387104004","https://openalex.org/W3047671631","https://openalex.org/W1540588256","https://openalex.org/W4378191048"],"abstract_inverted_index":{"Microcalcifications":[0],"are":[1,106],"the":[2,37,52],"earliest":[3],"sign":[4],"of":[5,86],"breast":[6],"carcinoma.":[7],"Their":[8],"typical":[9],"size":[10],"is":[11,16,19,89,115],"about":[12],"1":[13],"mm,":[14],"which":[15],"why":[17],"it":[18],"difficult":[20],"to":[21,65,80,90,117],"detect":[22],"for":[23],"an":[24],"expert.":[25],"Therefore,":[26],"a":[27,95],"tool":[28],"that":[29,40],"eases":[30],"their":[31,81],"visualization":[32],"becomes":[33,54],"relevant.":[34],"Segmentation":[35],"gives":[36],"candidate":[38],"areas":[39],"could":[41],"contain":[42],"microcalcifications.":[43],"A":[44],"preprocessing":[45],"step":[46],"can":[47],"improve":[48,118],"segmentation":[49],"performance":[50,97,119],"but":[51,112],"algorithm":[53],"database":[55],"dependent.":[56],"This":[57],"paper":[58,88],"compares":[59],"four":[60],"commonly":[61],"used":[62],"thresholding":[63],"techniques":[64],"segment":[66],"mammography":[67,102],"images":[68],"having":[69],"sections":[70],"divided":[71],"in":[72,98],"three":[73],"groups:":[74],"obvious,":[75],"subtle":[76,121],"and":[77,109,122],"clusters;":[78],"due":[79],"microcalcification":[82],"contents.":[83],"The":[84],"purpose":[85],"this":[87],"show":[91],"what":[92],"technique":[93],"has":[94],"better":[96],"special":[99],"relation":[100],"with":[101],"images.":[103],"Best":[104],"performers":[105],"Entropy":[107],"(68.8%),":[108],"Intermodes":[110],"(50.9%),":[111],"further":[113],"research":[114],"needed":[116],"on":[120],"cluster":[123],"microcalcifications":[124],"considering":[125],"non-bimodal":[126],"histograms.":[127]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}