{"id":"https://openalex.org/W2080542999","doi":"https://doi.org/10.1145/2534329.2534371","title":"A novel cerebrovascular segmentation approach based on Markov random field and particle swarm optimization algorithm","display_name":"A novel cerebrovascular segmentation approach based on Markov random field and particle swarm optimization algorithm","publication_year":2013,"publication_date":"2013-11-17","ids":{"openalex":"https://openalex.org/W2080542999","doi":"https://doi.org/10.1145/2534329.2534371","mag":"2080542999"},"language":"en","primary_location":{"id":"doi:10.1145/2534329.2534371","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2534329.2534371","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry","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/A5033411537","display_name":"Rong-Fei Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongfei Cao","raw_affiliation_strings":["Beijing Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024691662","display_name":"Xingce Wang","orcid":"https://orcid.org/0000-0002-3177-8902"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingce Wang","raw_affiliation_strings":["Beijing Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111486260","display_name":"Zhongke Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongke Wu","raw_affiliation_strings":["Beijing Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021263022","display_name":"Mingquan Zhou","orcid":"https://orcid.org/0000-0002-6354-3948"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingquan Zhou","raw_affiliation_strings":["Beijing Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002734812","display_name":"Yun Tian","orcid":"https://orcid.org/0000-0001-5574-2325"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Tian","raw_affiliation_strings":["Beijing Normal University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100446436","display_name":"Xinyu Liu","orcid":"https://orcid.org/0000-0002-5180-6958"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Liu","raw_affiliation_strings":["Chinese Academy of Science, Beijing, China","[Chinese Academy of Science, Beijing, China]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Science, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"[Chinese Academy of Science, Beijing, China]","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"295","last_page":"298"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9912999868392944,"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/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.6319095492362976},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.6085249781608582},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5974358916282654},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.5393050312995911},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5298490524291992},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5268974304199219},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4826693832874298},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4779410660266876},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4458836615085602},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4298483729362488},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.42401155829429626},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4151558578014374},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.09474799036979675},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07224991917610168}],"concepts":[{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.6319095492362976},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.6085249781608582},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5974358916282654},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.5393050312995911},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5298490524291992},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5268974304199219},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4826693832874298},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4779410660266876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4458836615085602},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4298483729362488},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.42401155829429626},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4151558578014374},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.09474799036979675},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07224991917610168},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2534329.2534371","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2534329.2534371","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.5600000023841858}],"awards":[{"id":"https://openalex.org/G4414736133","display_name":null,"funder_award_id":"61271366, 61170170, 61003134, 61170203","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8852774750","display_name":null,"funder_award_id":"4081002","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null},{"id":"https://openalex.org/F4320326357","display_name":"People\u2019s Liberation Army Navy General Hospital","ror":"https://ror.org/036dyz052"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1482926148","https://openalex.org/W1874690585","https://openalex.org/W1899329334","https://openalex.org/W1974954013","https://openalex.org/W1976060261","https://openalex.org/W1986640343","https://openalex.org/W1991140840","https://openalex.org/W2057875203","https://openalex.org/W2097073572","https://openalex.org/W2104095591","https://openalex.org/W2109364787","https://openalex.org/W2117661433","https://openalex.org/W2129534965","https://openalex.org/W2139478903"],"related_works":["https://openalex.org/W2107628111","https://openalex.org/W2394004323","https://openalex.org/W4233585817","https://openalex.org/W2016045932","https://openalex.org/W1675950995","https://openalex.org/W2188882668","https://openalex.org/W2004379491","https://openalex.org/W2088323302","https://openalex.org/W1998269854","https://openalex.org/W2083140487"],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,41,54,78,96],"solve":[3],"the":[4,56,80,87,94,98,107,126,136],"complex":[5],"problems":[6],"of":[7,58,83,101,141],"segmenting":[8],"cerebral":[9,44],"vessels":[10],"with":[11,93,125],"many":[12],"branches,":[13],"small":[14,116],"shape,":[15],"special":[16],"position":[17],"and":[18,30,72,91,118,122,139],"various":[19],"patterns,":[20],"a":[21,62],"novel":[22],"approach":[23],"based":[24],"on":[25,110],"markov":[26],"random":[27],"field":[28],"(MRF)":[29],"particle":[31],"swarm":[32],"optimization":[33],"algorithm":[34],"(PSO)":[35],"is":[36,52,76,89],"proposed":[37],"in":[38,135],"this":[39],"paper":[40],"accurately":[42],"segment":[43],"vessels.":[45],"Firstly,":[46],"an":[47],"improved":[48],"nonlocal":[49],"means":[50],"filtering":[51],"used":[53,77],"reduce":[55],"interference":[57],"correlated":[59],"noise.":[60],"Then":[61],"new":[63],"finite":[64],"mixture":[65],"model":[66],"(FMM)":[67],"-":[68],"two":[69],"Gaussian":[70],"distribution":[71,75],"one":[73],"Rayleigh":[74],"fit":[79],"intensity":[81],"histogram":[82],"brain":[84],"tissues.":[85],"Moreover,":[86],"MRF":[88],"constructed":[90],"fused":[92],"PSO":[95],"obtain":[97],"optimal":[99],"parameters":[100],"FMM.":[102],"The":[103,129],"experimental":[104],"results":[105],"verified":[106],"high":[108,120],"accuracy":[109],"cerebrovascular":[111,142],"segmentation":[112],"especially":[113],"for":[114],"those":[115],"vessels,":[117],"relative":[119],"robustness":[121],"generalization":[123],"comparing":[124],"classical":[127],"methods.":[128],"method":[130],"can":[131],"be":[132],"widely":[133],"applied":[134],"clinical":[137],"prevention":[138],"diagnosis":[140],"diseases.":[143]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
