{"id":"https://openalex.org/W2084719208","doi":"https://doi.org/10.1109/gamenets.2014.7043717","title":"A large margin nearest cluster metric based semisupervised clustering algorithm for brain fibers","display_name":"A large margin nearest cluster metric based semisupervised clustering algorithm for brain fibers","publication_year":2014,"publication_date":"2014-11-01","ids":{"openalex":"https://openalex.org/W2084719208","doi":"https://doi.org/10.1109/gamenets.2014.7043717","mag":"2084719208"},"language":"en","primary_location":{"id":"doi:10.1109/gamenets.2014.7043717","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gamenets.2014.7043717","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2014 5th International Conference on Game Theory for Networks","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/A5012217615","display_name":"Meiyu Huang","orcid":"https://orcid.org/0000-0002-7513-1764"},"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"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meiyu Huang","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China","The Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]},{"raw_affiliation_string":"The Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008558592","display_name":"Yiqiang Chen","orcid":"https://orcid.org/0000-0002-8407-0780"},"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":"Yiqiang Chen","raw_affiliation_strings":["The Beijing Key Laboratory of Mobile Computing and Pervasive Device, Chinese Academy of Sciences, Beijing, China","The Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Beijing Key Laboratory of Mobile Computing and Pervasive Device, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"The Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048774346","display_name":"Junfa Liu","orcid":"https://orcid.org/0000-0003-0340-9824"},"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":"Junfa Liu","raw_affiliation_strings":["The Beijing Key Laboratory of Mobile Computing and Pervasive Device, Chinese Academy of Sciences, Beijing, China","The Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Beijing Key Laboratory of Mobile Computing and Pervasive Device, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"The Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042941682","display_name":"Wen Ji","orcid":"https://orcid.org/0000-0001-6895-3404"},"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":"Wen Ji","raw_affiliation_strings":["The Beijing Key Laboratory of Mobile Computing and Pervasive Device, Chinese Academy of Sciences, Beijing, China","The Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Beijing Key Laboratory of Mobile Computing and Pervasive Device, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366"]},{"raw_affiliation_string":"The Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3952,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.70925694,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9972000122070312,"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"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9972000122070312,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9969000220298767,"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/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.9901999831199646,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7682945728302002},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.7455467581748962},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6779162287712097},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6538158059120178},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5878797769546509},{"id":"https://openalex.org/keywords/fiber","display_name":"Fiber","score":0.5647169947624207},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.5484283566474915},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5376855731010437},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22372236847877502},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.0923478901386261},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06520110368728638}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7682945728302002},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.7455467581748962},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6779162287712097},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6538158059120178},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5878797769546509},{"id":"https://openalex.org/C519885992","wikidata":"https://www.wikidata.org/wiki/Q161","display_name":"Fiber","level":2,"score":0.5647169947624207},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.5484283566474915},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5376855731010437},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22372236847877502},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0923478901386261},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06520110368728638},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gamenets.2014.7043717","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gamenets.2014.7043717","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2014 5th International Conference on Game Theory for Networks","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":20,"referenced_works":["https://openalex.org/W1498782169","https://openalex.org/W1564583583","https://openalex.org/W1596382552","https://openalex.org/W1977556410","https://openalex.org/W2102524069","https://openalex.org/W2106053110","https://openalex.org/W2117154949","https://openalex.org/W2129390822","https://openalex.org/W2132347401","https://openalex.org/W2134089414","https://openalex.org/W2149230623","https://openalex.org/W2159583439","https://openalex.org/W2912522929","https://openalex.org/W6630018080","https://openalex.org/W6633864139","https://openalex.org/W6635376254","https://openalex.org/W6675528751","https://openalex.org/W6675751002","https://openalex.org/W6677328822","https://openalex.org/W6679849079"],"related_works":["https://openalex.org/W3125011624","https://openalex.org/W1508631387","https://openalex.org/W2370917603","https://openalex.org/W2017776670","https://openalex.org/W2952760143","https://openalex.org/W2347897961","https://openalex.org/W2979236518","https://openalex.org/W2358318464","https://openalex.org/W2997457842","https://openalex.org/W1997431798"],"abstract_inverted_index":{"Biomedical":[0],"science":[1],"has":[2,18],"proven":[3],"that":[4,59,125],"human":[5],"brain":[6,25,35,39,57,63,71,116,132],"fiber":[7,101,117,133],"tracts":[8,102],"have":[9],"correspondent":[10],"relationship":[11],"with":[12,66],"the":[13,24,31,50,54,115,121,129],"physiological":[14],"functions,":[15],"and":[16,45],"it":[17],"important":[19],"medical":[20],"significance":[21],"to":[22,136],"cluster":[23],"fibers":[26,40,58,64,72],"accurately.":[27],"But":[28],"because":[29],"of":[30,34,53,56,62,108,131],"huge":[32],"number":[33],"fibers,":[36],"manually":[37],"segmenting":[38],"will":[41],"result":[42],"in":[43],"time":[44],"effort":[46],"consuming.":[47],"And":[48],"for":[49],"extreme":[51],"complexity":[52],"distribution":[55],"different":[60],"types":[61],"cross":[65],"each":[67],"other,":[68],"automatically":[69],"mapping":[70],"using":[73],"unsupervised":[74],"clustering":[75,92],"algorithms":[76],"cannot":[77],"give":[78],"satisfactory":[79],"results.":[80],"This":[81],"work":[82],"proposed":[83],"a":[84,105],"Large":[85],"Margin":[86],"Nearest":[87],"Cluster":[88],"metric":[89],"based":[90],"semi-supervised":[91],"algorithm":[93],"called":[94],"LISODATA,":[95],"which":[96],"can":[97],"better":[98],"separate":[99],"crossing":[100],"by":[103,120],"employing":[104],"small":[106],"amount":[107],"supervised":[109],"information.":[110],"The":[111],"experimental":[112],"results":[113],"on":[114],"dataset":[118],"provided":[119],"2009":[122],"PBC":[123],"demonstrated":[124],"LISODATA":[126],"could":[127],"improve":[128],"purity":[130],"clusters":[134],"compared":[135],"ISODATA.":[137]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
