{"id":"https://openalex.org/W2181862262","doi":"https://doi.org/10.1109/mmsp.2015.7340801","title":"Automatic liver segmentation from CT images using latent semantic indexing","display_name":"Automatic liver segmentation from CT images using latent semantic indexing","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W2181862262","doi":"https://doi.org/10.1109/mmsp.2015.7340801","mag":"2181862262"},"language":"en","primary_location":{"id":"doi:10.1109/mmsp.2015.7340801","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp.2015.7340801","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP)","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/A5052266602","display_name":"Chun-Yao Hsieh","orcid":null},"institutions":[{"id":"https://openalex.org/I153512688","display_name":"National Taiwan Ocean University","ror":"https://ror.org/03bvvnt49","country_code":"TW","type":"education","lineage":["https://openalex.org/I153512688"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Chun-Yao Hsieh","raw_affiliation_strings":["Department of Computer Science & Engineering, National Taiwan Ocean University, Keelung, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, National Taiwan Ocean University, Keelung, Taiwan","institution_ids":["https://openalex.org/I153512688"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101839507","display_name":"Shyi\u2010Chyi Cheng","orcid":"https://orcid.org/0000-0003-4752-0460"},"institutions":[{"id":"https://openalex.org/I153512688","display_name":"National Taiwan Ocean University","ror":"https://ror.org/03bvvnt49","country_code":"TW","type":"education","lineage":["https://openalex.org/I153512688"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shyi-Chyi Cheng","raw_affiliation_strings":["Department of Computer Science & Engineering, National Taiwan Ocean University, Keelung, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, National Taiwan Ocean University, Keelung, Taiwan","institution_ids":["https://openalex.org/I153512688"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103129411","display_name":"Chin-Chun Chang","orcid":"https://orcid.org/0000-0002-4566-8683"},"institutions":[{"id":"https://openalex.org/I153512688","display_name":"National Taiwan Ocean University","ror":"https://ror.org/03bvvnt49","country_code":"TW","type":"education","lineage":["https://openalex.org/I153512688"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chin-Chun Chang","raw_affiliation_strings":["Department of Computer Science & Engineering, National Taiwan Ocean University, Keelung, Taiwan"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, National Taiwan Ocean University, Keelung, Taiwan","institution_ids":["https://openalex.org/I153512688"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057583966","display_name":"Chin-Lang Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210111603","display_name":"Keelung Chang Gung Memorial Hospital","ror":"https://ror.org/020dg9f27","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I4210111603"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chin-Lang Lin","raw_affiliation_strings":["Liver Research Unit, Chang Gung Memorial Hospital, Keelung, Taiwan"],"affiliations":[{"raw_affiliation_string":"Liver Research Unit, Chang Gung Memorial Hospital, Keelung, Taiwan","institution_ids":["https://openalex.org/I4210111603"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5052266602"],"corresponding_institution_ids":["https://openalex.org/I153512688"],"apc_list":null,"apc_paid":null,"fwci":0.3997,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.69185553,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9995999932289124,"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":0.9995999932289124,"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/T10862","display_name":"AI in cancer detection","score":0.9948999881744385,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9944999814033508,"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/segmentation","display_name":"Segmentation","score":0.7519357204437256},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7349050641059875},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6576244831085205},{"id":"https://openalex.org/keywords/hough-transform","display_name":"Hough transform","score":0.549896240234375},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.533409595489502},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4959317147731781},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.49238288402557373},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.47632986307144165},{"id":"https://openalex.org/keywords/landmark","display_name":"Landmark","score":0.4698438048362732},{"id":"https://openalex.org/keywords/level-set","display_name":"Level set (data structures)","score":0.43333035707473755},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4266390800476074},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4261319935321808},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22840160131454468}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7519357204437256},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7349050641059875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6576244831085205},{"id":"https://openalex.org/C200518788","wikidata":"https://www.wikidata.org/wiki/Q195076","display_name":"Hough transform","level":3,"score":0.549896240234375},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.533409595489502},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4959317147731781},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.49238288402557373},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.47632986307144165},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.4698438048362732},{"id":"https://openalex.org/C153008295","wikidata":"https://www.wikidata.org/wiki/Q6535093","display_name":"Level set (data structures)","level":2,"score":0.43333035707473755},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4266390800476074},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4261319935321808},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22840160131454468}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mmsp.2015.7340801","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp.2015.7340801","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W22745672","https://openalex.org/W1548531823","https://openalex.org/W1972344168","https://openalex.org/W1979393293","https://openalex.org/W1996565856","https://openalex.org/W2002801995","https://openalex.org/W2021422668","https://openalex.org/W2038952578","https://openalex.org/W2049981393","https://openalex.org/W2071555444","https://openalex.org/W2081706464","https://openalex.org/W2094944418","https://openalex.org/W2129663601","https://openalex.org/W2147152072","https://openalex.org/W2153431772","https://openalex.org/W2165734775","https://openalex.org/W2275209358","https://openalex.org/W2533885885","https://openalex.org/W6668499391","https://openalex.org/W6728608369"],"related_works":["https://openalex.org/W2056853153","https://openalex.org/W2057559274","https://openalex.org/W2005087563","https://openalex.org/W2373659438","https://openalex.org/W2392905701","https://openalex.org/W2149987068","https://openalex.org/W1879755808","https://openalex.org/W2986132491","https://openalex.org/W2171653019","https://openalex.org/W2186275670"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,129,145,169],"present":[4],"an":[5],"indexing":[6],"structure":[7],"of":[8,17,66,72,76,87,119,122,125,196,206,212],"data-driven":[9],"cuboid":[10],"patterns":[11],"to":[12,37,55,83,160,175,192],"speed":[13],"up":[14],"the":[15,28,57,61,70,73,84,131,147,166,171,194,197,203,207],"process":[16],"liver":[18,39,88,133,156,173,186],"detection":[19],"and":[20,141,181,215],"segmentation":[21,40,100,187,213],"from":[22,41],"computed":[23],"tomography":[24],"(CT)":[25],"scans":[26,43],"using":[27],"cube-based":[29,132],"generalized":[30],"Hough":[31,139],"transform":[32],"(CGHT).":[33],"Most":[34],"existing":[35],"approaches":[36],"automatic":[38,99],"CT":[42,91,109],"use":[44],"a":[45,52,80,97,107,152],"statistical":[46,163],"shape":[47,75,157,174],"model":[48,150],"(SSM)":[49],"integrated":[50],"with":[51,117],"searching":[53],"algorithm":[54],"recover":[56],"deformation.":[58],"However,":[59],"establishing":[60],"correspondences":[62],"among":[63],"landmark":[64],"points":[65],"training":[67],"shapes":[68,89,134],"for":[69,155],"construction":[71],"average":[74],"SSM":[77],"remains":[78],"as":[79],"challenge":[81,188],"due":[82],"high":[85],"variation":[86],"in":[90,135,210],"scans.":[92],"The":[93,183],"proposed":[94,198,208],"method":[95,101,209],"is":[96,111],"fully":[98],"that":[102],"combines":[103],"four":[104],"steps.":[105],"Firstly,":[106],"test":[108],"volume":[110],"partitioned":[112],"into":[113,165],"multiple":[114],"non-overlapped":[115],"sub-volumes":[116,137],"each":[118],"them":[120],"consisting":[121],"variable":[123],"numbers":[124],"consecutive":[126],"slices.":[127],"Secondly,":[128],"locate":[130],"all":[136],"via":[138],"voting":[140],"dynamic":[142],"programming.":[143],"Thirdly,":[144],"construct":[146],"basic":[148],"3D":[149,172],"through":[151],"level-set":[153],"framework":[154],"segmentation.":[158],"Finally,":[159],"introduce":[161],"neighbors":[162],"analysis":[164],"above":[167],"model,":[168],"deform":[170],"overcome":[176],"disturbances":[177],"caused":[178],"by":[179],"noise":[180],"inhomogeneity.":[182],"MICCAI":[184],"2007":[185],"datasets":[189],"are":[190],"used":[191],"verify":[193],"effectiveness":[195],"method.":[199],"Experimental":[200],"results":[201],"demonstrate":[202],"good":[204],"performance":[205],"terms":[211],"accuracy":[214],"execution":[216],"speed.":[217]},"counts_by_year":[{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
