{"id":"https://openalex.org/W2775362455","doi":"https://doi.org/10.1109/smc.2017.8122840","title":"Evaluation of a classification method for MR image segmentation","display_name":"Evaluation of a classification method for MR image segmentation","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2775362455","doi":"https://doi.org/10.1109/smc.2017.8122840","mag":"2775362455"},"language":"en","primary_location":{"id":"doi:10.1109/smc.2017.8122840","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc.2017.8122840","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5040547853","display_name":"Yoshihiko Kubota","orcid":"https://orcid.org/0009-0001-7959-2787"},"institutions":[{"id":"https://openalex.org/I165522056","display_name":"Tokyo Denki University","ror":"https://ror.org/01pa62v70","country_code":"JP","type":"education","lineage":["https://openalex.org/I165522056"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yoshihiko Kubota","raw_affiliation_strings":["School of Information Environment, Tokyo Denki University, Inzai, Japan"],"affiliations":[{"raw_affiliation_string":"School of Information Environment, Tokyo Denki University, Inzai, Japan","institution_ids":["https://openalex.org/I165522056"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112624843","display_name":"Setsuo Tsuruta","orcid":null},"institutions":[{"id":"https://openalex.org/I165522056","display_name":"Tokyo Denki University","ror":"https://ror.org/01pa62v70","country_code":"JP","type":"education","lineage":["https://openalex.org/I165522056"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Setsuo Tsuruta","raw_affiliation_strings":["School of Information Environment, Tokyo Denki University, Inzai, Japan"],"affiliations":[{"raw_affiliation_string":"School of Information Environment, Tokyo Denki University, Inzai, Japan","institution_ids":["https://openalex.org/I165522056"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042142624","display_name":"Syoji Kobashi","orcid":"https://orcid.org/0000-0003-3659-4114"},"institutions":[{"id":"https://openalex.org/I84059937","display_name":"Hyogo University","ror":"https://ror.org/024pdem44","country_code":"JP","type":"education","lineage":["https://openalex.org/I84059937"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Syoji Kobashi","raw_affiliation_strings":["Department of Computer Engineering, Hyogo University, Himeji, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Hyogo University, Himeji, Japan","institution_ids":["https://openalex.org/I84059937"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112359845","display_name":"Yoshitaka Sakurai","orcid":null},"institutions":[{"id":"https://openalex.org/I16656306","display_name":"Meiji University","ror":"https://ror.org/02rqvrp93","country_code":"JP","type":"education","lineage":["https://openalex.org/I16656306"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshitaka Sakurai","raw_affiliation_strings":["School of Interdisciplinary Mathematical Sciences, Meiji University, Nakano, Japan"],"affiliations":[{"raw_affiliation_string":"School of Interdisciplinary Mathematical Sciences, Meiji University, Nakano, Japan","institution_ids":["https://openalex.org/I16656306"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086063823","display_name":"Rainer Knauf","orcid":"https://orcid.org/0000-0001-8795-6360"},"institutions":[{"id":"https://openalex.org/I119449181","display_name":"Technische Universit\u00e4t Ilmenau","ror":"https://ror.org/01weqhp73","country_code":"DE","type":"education","lineage":["https://openalex.org/I119449181"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Rainer Knauf","raw_affiliation_strings":["Dept. of Computer Science and Automation, Technische Universit\u00e4t Ilmenau, Ilmenau, Germany"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science and Automation, Technische Universit\u00e4t Ilmenau, Ilmenau, Germany","institution_ids":["https://openalex.org/I119449181"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5040547853"],"corresponding_institution_ids":["https://openalex.org/I165522056"],"apc_list":null,"apc_paid":null,"fwci":0.7801,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.80238466,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1581","last_page":"1586"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10906","display_name":"AI-based Problem Solving and Planning","score":0.9958999752998352,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.9958999752998352,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9894000291824341,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9828000068664551,"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":0.7508881092071533},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6749287843704224},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6703886985778809},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6484113335609436},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.636624276638031},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.6333839297294617},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5261556506156921},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.5190702080726624},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.48140549659729004},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44750910997390747},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4292908310890198},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4165725111961365},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.4131573438644409},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.41119492053985596},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23725289106369019}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7508881092071533},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6749287843704224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6703886985778809},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6484113335609436},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.636624276638031},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.6333839297294617},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5261556506156921},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5190702080726624},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.48140549659729004},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44750910997390747},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4292908310890198},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4165725111961365},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.4131573438644409},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.41119492053985596},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23725289106369019},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc.2017.8122840","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc.2017.8122840","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1504886722","https://openalex.org/W1565377632","https://openalex.org/W2013836735","https://openalex.org/W2057836984","https://openalex.org/W2083775921","https://openalex.org/W2101123196","https://openalex.org/W2116099700","https://openalex.org/W2321644719","https://openalex.org/W2482589566","https://openalex.org/W2496883485","https://openalex.org/W6677287112"],"related_works":["https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W3144569342","https://openalex.org/W4313052709","https://openalex.org/W2945274617","https://openalex.org/W2022929107","https://openalex.org/W2055202857","https://openalex.org/W1999008862","https://openalex.org/W4205800335","https://openalex.org/W2758994127"],"abstract_inverted_index":{"The":[0,91],"paper":[1],"introduces":[2],"a":[3,58,83],"proposal":[4],"for":[5],"an":[6,29],"automated":[7],"magnetic":[8],"resonance":[9],"(MR)":[10],"image":[11,35,40,78],"segmentation":[12],"called":[13],"Case-Based":[14],"Genetic":[15],"Algorithm":[16],"Location-Dependent":[17],"Image":[18],"Classification":[19],"(CBGA-LDIC)":[20],"and":[21,87,114,130,140],"presents":[22],"its":[23],"evaluation":[24],"results.":[25],"This":[26],"method":[27,92,123],"finds":[28],"appropriate":[30],"cell":[31],"set":[32,84],"towards":[33],"efficient":[34],"segmentation.":[36],"It":[37],"uses":[38],"location-dependent":[39,64],"classification":[41],"(LDIC),":[42],"which":[43,61],"is":[44,57,68,93],"integrated":[45],"by":[46,70],"genetic":[47],"algorithm":[48],"(GA)":[49],"combined":[50],"with":[51],"case":[52,117],"based":[53],"reasoning":[54],"(CB).":[55],"LDIC":[56],"local":[59],"heuristic,":[60],"defines":[62],"multiple":[63],"classifiers.":[65,90],"Each":[66],"classifier":[67],"trained":[69],"Gaussian":[71],"mixture":[72],"model.":[73],"CBGA-LDIC":[74],"decomposes":[75],"the":[76],"whole":[77],"into":[79],"some":[80,135],"cells,":[81,86],"makes":[82],"of":[85,110],"then":[88],"trains":[89],"applied":[94],"to":[95,131],"knee":[96],"bones,":[97],"because":[98],"these":[99],"bone":[100],"formations":[101],"are":[102,112,143],"similar":[103],"in":[104,116,145],"their":[105,141],"location.":[106],"Therefore,":[107],"good":[108],"combinations":[109],"cells":[111],"useful":[113],"stored":[115],"bases.":[118],"To":[119],"show,":[120],"that":[121,127],"this":[122,146],"produces":[124],"better":[125],"results":[126,142],"other":[128],"ones":[129],"find":[132],"optimal":[133],"parameters,":[134],"experiments":[136],"have":[137],"been":[138],"performed":[139],"presented":[144],"paper.":[147]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
