{"id":"https://openalex.org/W2940118025","doi":"https://doi.org/10.1145/3309074.3309123","title":"Improved active contour model for multi-phase MR image segmentation and bias field correction","display_name":"Improved active contour model for multi-phase MR image segmentation and bias field correction","publication_year":2019,"publication_date":"2019-01-19","ids":{"openalex":"https://openalex.org/W2940118025","doi":"https://doi.org/10.1145/3309074.3309123","mag":"2940118025"},"language":"en","primary_location":{"id":"doi:10.1145/3309074.3309123","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3309074.3309123","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd International Conference on Cryptography, Security and Privacy","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/A5090906323","display_name":"Yunyun Yang","orcid":"https://orcid.org/0000-0002-0488-7652"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunyun Yang","raw_affiliation_strings":["Harbin Institute of Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100395314","display_name":"Wenjing Jia","orcid":"https://orcid.org/0000-0002-0940-3338"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjing Jia","raw_affiliation_strings":["Harbin Institute of Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018722102","display_name":"Dongcai Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongcai Tian","raw_affiliation_strings":["Harbin Institute of Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I204983213"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"242","last_page":"246"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9987999796867371,"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":0.9987999796867371,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9660000205039978,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9606999754905701,"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/active-contour-model","display_name":"Active contour model","score":0.7353286743164062},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7276725769042969},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7157535552978516},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6598012447357178},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.6475803852081299},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6236743927001953},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.6071221232414246},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5856932401657104},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.561844527721405},{"id":"https://openalex.org/keywords/phase","display_name":"Phase (matter)","score":0.4797847867012024},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47915929555892944},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.44835150241851807},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4222191572189331},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.21768328547477722},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21607375144958496},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.12592685222625732},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08086895942687988},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.07154574990272522}],"concepts":[{"id":"https://openalex.org/C112353826","wikidata":"https://www.wikidata.org/wiki/Q127313","display_name":"Active contour model","level":4,"score":0.7353286743164062},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7276725769042969},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7157535552978516},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6598012447357178},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.6475803852081299},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6236743927001953},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.6071221232414246},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5856932401657104},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.561844527721405},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.4797847867012024},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47915929555892944},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.44835150241851807},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4222191572189331},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.21768328547477722},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21607375144958496},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.12592685222625732},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08086895942687988},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.07154574990272522},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3309074.3309123","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3309074.3309123","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd International Conference on Cryptography, Security and Privacy","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1605048340","https://openalex.org/W1989532447","https://openalex.org/W2081163504","https://openalex.org/W2091187164","https://openalex.org/W2116040950","https://openalex.org/W2132116135","https://openalex.org/W2135095945","https://openalex.org/W2139478903","https://openalex.org/W2142058898","https://openalex.org/W2202737976","https://openalex.org/W2466034989"],"related_works":["https://openalex.org/W2387003628","https://openalex.org/W123102278","https://openalex.org/W2081609930","https://openalex.org/W2365596436","https://openalex.org/W1522196789","https://openalex.org/W4210537690","https://openalex.org/W2885157826","https://openalex.org/W2159463658","https://openalex.org/W4388208420","https://openalex.org/W2051067977"],"abstract_inverted_index":{"Magnetic":[0],"resonance":[1,57],"imaging":[2,9],"(MRI)":[3],"has":[4],"been":[5],"applied":[6],"in":[7],"the":[8,25,31,43,48,51,62,70,79,90,97,102,109,115,123,132],"of":[10,13,27,34,50,105],"all":[11],"tissues":[12,99],"human":[14],"body.":[15],"It":[16],"is":[17,37,135],"an":[18,82],"important":[19],"method":[20],"for":[21,39],"doctors":[22,40],"to":[23,41,47],"analyze":[24],"cause":[26],"diseases.":[28],"In":[29,76],"particular,":[30],"accurate":[32,137],"segmentation":[33,73],"MR":[35,71,106],"images":[36,59,107],"significant":[38],"diagnose":[42],"etiology.":[44],"However,":[45],"due":[46],"limitation":[49],"MRI":[52],"equipment":[53],"and":[54,65,100,119,127,138],"technology,":[55],"magnetic":[56],"(MR)":[58],"always":[60],"have":[61],"intensity":[63],"inhomogeneity":[64],"fuzzy":[66],"edges,":[67],"which":[68,93],"makes":[69],"image":[72],"more":[74,136],"difficult.":[75],"this":[77],"paper,":[78],"authors":[80,113],"propose":[81],"improved":[83],"multi-phase":[84,116],"active":[85],"contour":[86],"model":[87,134],"based":[88],"on":[89],"clustering":[91],"method,":[92,126],"can":[94],"accurately":[95],"segment":[96],"multiple":[98],"correct":[101],"bias":[103],"field":[104],"at":[108],"same":[110],"time.":[111],"The":[112],"give":[114],"energy":[117],"functional":[118],"minimize":[120],"it":[121],"by":[122],"split":[124],"Bregman":[125],"experimental":[128],"results":[129],"show":[130],"that":[131],"proposed":[133],"efficient.":[139]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
