{"id":"https://openalex.org/W2890845820","doi":"https://doi.org/10.1145/3239264.3239276","title":"Texture Segmentation of Urinary Sediment Image based on a Weighted Gaussian Mixture Model with Markov Random Fields","display_name":"Texture Segmentation of Urinary Sediment Image based on a Weighted Gaussian Mixture Model with Markov Random Fields","publication_year":2018,"publication_date":"2018-06-23","ids":{"openalex":"https://openalex.org/W2890845820","doi":"https://doi.org/10.1145/3239264.3239276","mag":"2890845820"},"language":"en","primary_location":{"id":"doi:10.1145/3239264.3239276","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3239264.3239276","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 7th International Conference on Bioinformatics and Biomedical Science","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/A5036390761","display_name":"Xiaoming Jiang","orcid":"https://orcid.org/0000-0002-8184-1578"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoming Jiang","raw_affiliation_strings":["College of Bio-information, Chongqing University of Posts and Telecommunication, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Bio-information, Chongqing University of Posts and Telecommunication, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076837256","display_name":"Fuqu Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuqu Chen","raw_affiliation_strings":["College of Bio-information, Chongqing University of Posts and Telecommunication, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Bio-information, Chongqing University of Posts and Telecommunication, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100417933","display_name":"Qianqian Chen","orcid":"https://orcid.org/0000-0001-9071-0791"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qianqian Chen","raw_affiliation_strings":["College of Bio-information, Chongqing University of Posts and Telecommunication, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Bio-information, Chongqing University of Posts and Telecommunication, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087598944","display_name":"Miaomiao Si","orcid":null},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Miaomiao Si","raw_affiliation_strings":["College of Bio-information, Chongqing University of Posts and Telecommunication, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Bio-information, Chongqing University of Posts and Telecommunication, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100757829","display_name":"Wei Wang","orcid":"https://orcid.org/0000-0002-8598-0831"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wang","raw_affiliation_strings":["College of Bio-information, Chongqing University of Posts and Telecommunication, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Bio-information, Chongqing University of Posts and Telecommunication, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5036390761"],"corresponding_institution_ids":["https://openalex.org/I10535382"],"apc_list":null,"apc_paid":null,"fwci":0.2089,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.55197794,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"82","last_page":"87"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9519000053405762,"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"}},"topics":[{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9519000053405762,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9509000182151794,"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/urinary-sediment","display_name":"Urinary sediment","score":0.7039015889167786},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6646149158477783},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6385520100593567},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5795314908027649},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5402142405509949},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5224272608757019},{"id":"https://openalex.org/keywords/magnification","display_name":"Magnification","score":0.5042587518692017},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4709635376930237},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4673581123352051},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.4525439739227295},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4397367835044861},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.4371107518672943},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4349300265312195},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34281986951828003},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.10147643089294434}],"concepts":[{"id":"https://openalex.org/C2910111155","wikidata":"https://www.wikidata.org/wiki/Q245639","display_name":"Urinary sediment","level":3,"score":0.7039015889167786},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6646149158477783},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6385520100593567},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5795314908027649},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5402142405509949},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5224272608757019},{"id":"https://openalex.org/C4144372","wikidata":"https://www.wikidata.org/wiki/Q675287","display_name":"Magnification","level":2,"score":0.5042587518692017},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4709635376930237},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4673581123352051},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.4525439739227295},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4397367835044861},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.4371107518672943},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4349300265312195},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34281986951828003},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.10147643089294434},{"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},{"id":"https://openalex.org/C2780026642","wikidata":"https://www.wikidata.org/wiki/Q40924","display_name":"Urine","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3239264.3239276","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3239264.3239276","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2018 7th International Conference on Bioinformatics and Biomedical Science","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":13,"referenced_works":["https://openalex.org/W1975912079","https://openalex.org/W1993373209","https://openalex.org/W1997063559","https://openalex.org/W2013985817","https://openalex.org/W2093476379","https://openalex.org/W2129526018","https://openalex.org/W2147289653","https://openalex.org/W2166476553","https://openalex.org/W2288240035","https://openalex.org/W4238127125","https://openalex.org/W4241385190","https://openalex.org/W4255443310","https://openalex.org/W4300802661"],"related_works":["https://openalex.org/W2041117173","https://openalex.org/W4256609757","https://openalex.org/W2152595177","https://openalex.org/W1810141276","https://openalex.org/W2005715326","https://openalex.org/W2418534670","https://openalex.org/W2022127494","https://openalex.org/W2047186806","https://openalex.org/W2373481280","https://openalex.org/W2015790018"],"abstract_inverted_index":{"In":[0,36],"clinical":[1],"laboratory":[2],"studies,":[3],"it":[4,171],"is":[5,91,143,184],"of":[6,17,29,46,53,83,103,158,180],"importance":[7],"for":[8,26,43,73],"urinary":[9,30,162],"sediment":[10,48,163],"images":[11,23],"because":[12],"the":[13,22,27,44,51,68,74,77,81,89,100,104,108,122,130,139,150,156,188],"composition":[14],"and":[15,31,107,146,182],"quantity":[16],"specific":[18],"cells":[19,181],"contained":[20],"in":[21,34,76,88,97,165,187],"revealing":[24],"information":[25],"diagnosis":[28],"renal":[32],"diseases":[33],"humans.":[35],"this":[37,166],"paper,":[38],"we":[39],"propose":[40],"a":[41],"method":[42,61,157],"segmentation":[45,160],"urine":[47],"image":[49,90,164],"using":[50,155],"magnification":[52],"20-fold":[54],"microscopy":[55],"based":[56],"on":[57],"Markov":[58],"model.":[59,120],"This":[60],"selects":[62],"sum":[63],"average":[64,101],"feature":[65,126],"derived":[66],"from":[67],"spatial":[69],"gray":[70],"co-occurrence":[71],"matrix":[72,128],"classification":[75],"neighborhood":[78],"window":[79,131],"with":[80,99,110,149],"size":[82],"7\u00d77.":[84],"First,":[85],"each":[86],"pixel":[87],"evaluated":[92],"by":[93,117,154,176],"its":[94],"intensity":[95,102],"dispersion":[96,112],"comparison":[98],"7\u00d77":[105],"neighborhood,":[106],"pixels":[109],"higher":[111],"would":[113],"be":[114],"further":[115],"proceeded":[116],"Gaussian":[118],"mixture":[119],"Here":[121],"weights":[123],"are":[124],"designed":[125],"distance":[127],"within":[129],"to":[132,137],"obtain":[133],"similar,":[134],"so":[135],"as":[136],"re-estimate":[138],"features.":[140],"Edge":[141],"positioning":[142],"more":[144],"accurate":[145],"clear":[147],"compared":[148],"traditional":[151],"morphological":[152],"methods":[153],"texture":[159],"about":[161],"paper":[167],"which":[168],"can":[169],"make":[170],"avoids":[172],"cell":[173],"adhesion":[174],"caused":[175],"too":[177],"closer":[178],"proximity":[179],"there":[183],"no":[185],"glitch":[186],"target":[189],"area.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}