{"id":"https://openalex.org/W2193052550","doi":"https://doi.org/10.1117/12.2082255","title":"A supervoxel-based segmentation method for prostate MR images","display_name":"A supervoxel-based segmentation method for prostate MR images","publication_year":2015,"publication_date":"2015-03-20","ids":{"openalex":"https://openalex.org/W2193052550","doi":"https://doi.org/10.1117/12.2082255","mag":"2193052550","pmid":"https://pubmed.ncbi.nlm.nih.gov/26848206"},"language":"en","primary_location":{"id":"doi:10.1117/12.2082255","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2082255","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4736748","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020301327","display_name":"Zhiqiang Tian","orcid":"https://orcid.org/0000-0002-3669-3748"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhiqiang Tian","raw_affiliation_strings":["Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA","Emory Univ. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA","institution_ids":["https://openalex.org/I150468666"]},{"raw_affiliation_string":"Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035002271","display_name":"Lizhi Liu","orcid":"https://orcid.org/0009-0004-9683-038X"},"institutions":[{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"LiZhi Liu","raw_affiliation_strings":["Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA","Emory Univ. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA","institution_ids":["https://openalex.org/I150468666"]},{"raw_affiliation_string":"Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083707303","display_name":"Baowei Fei","orcid":"https://orcid.org/0000-0002-9123-9484"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]},{"id":"https://openalex.org/I150468666","display_name":"Emory University","ror":"https://ror.org/03czfpz43","country_code":"US","type":"education","lineage":["https://openalex.org/I150468666"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Baowei Fei","raw_affiliation_strings":["Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology","Georgia Institute of Technology (United States)","Emory Univ. (United States)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology","institution_ids":["https://openalex.org/I150468666"]},{"raw_affiliation_string":"Georgia Institute of Technology (United States)","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"Emory Univ. (United States)","institution_ids":["https://openalex.org/I150468666"]}]}],"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":12,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"9413","issue":null,"first_page":"941318","last_page":"941318"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9994000196456909,"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":0.9994000196456909,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9926999807357788,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9915000200271606,"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":0.8050464391708374},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7482002973556519},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6584857106208801},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5690083503723145},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5475484132766724},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5271658301353455},{"id":"https://openalex.org/keywords/prostate","display_name":"Prostate","score":0.4871901869773865},{"id":"https://openalex.org/keywords/prostate-cancer","display_name":"Prostate cancer","score":0.48714491724967957},{"id":"https://openalex.org/keywords/smoothness","display_name":"Smoothness","score":0.4761119782924652},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.45117443799972534},{"id":"https://openalex.org/keywords/level-set","display_name":"Level set (data structures)","score":0.4245694875717163},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4229063093662262},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4185223877429962},{"id":"https://openalex.org/keywords/cut","display_name":"Cut","score":0.41276848316192627},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1928292214870453},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.10721510648727417}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8050464391708374},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7482002973556519},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6584857106208801},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5690083503723145},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5475484132766724},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5271658301353455},{"id":"https://openalex.org/C2776235491","wikidata":"https://www.wikidata.org/wiki/Q9625","display_name":"Prostate","level":3,"score":0.4871901869773865},{"id":"https://openalex.org/C2780192828","wikidata":"https://www.wikidata.org/wiki/Q181257","display_name":"Prostate cancer","level":3,"score":0.48714491724967957},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.4761119782924652},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.45117443799972534},{"id":"https://openalex.org/C153008295","wikidata":"https://www.wikidata.org/wiki/Q6535093","display_name":"Level set (data structures)","level":2,"score":0.4245694875717163},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4229063093662262},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4185223877429962},{"id":"https://openalex.org/C5134670","wikidata":"https://www.wikidata.org/wiki/Q1626444","display_name":"Cut","level":4,"score":0.41276848316192627},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1928292214870453},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.10721510648727417},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.0},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1117/12.2082255","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2082255","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"},{"id":"pmid:26848206","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26848206","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of SPIE--the International Society for Optical Engineering","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:4736748","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4736748","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc SPIE Int Soc Opt Eng","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:4736748","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4736748","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proc SPIE Int Soc Opt Eng","raw_type":"Text"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.7300000190734863}],"awards":[{"id":"https://openalex.org/G7682172437","display_name":null,"funder_award_id":"R21 CA176684","funder_id":"https://openalex.org/F4320337351","funder_display_name":"National Cancer Institute"},{"id":"https://openalex.org/G8130889213","display_name":null,"funder_award_id":"P50 CA128301","funder_id":"https://openalex.org/F4320337351","funder_display_name":"National Cancer Institute"},{"id":"https://openalex.org/G8745886456","display_name":null,"funder_award_id":"R01 CA156775","funder_id":"https://openalex.org/F4320337351","funder_display_name":"National Cancer Institute"}],"funders":[{"id":"https://openalex.org/F4320306352","display_name":"Georgia Cancer Coalition","ror":"https://ror.org/0009gvn90"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337351","display_name":"National Cancer Institute","ror":"https://ror.org/040gcmg81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1980913318","https://openalex.org/W2012255096","https://openalex.org/W2037302265","https://openalex.org/W2052035603","https://openalex.org/W2057079596","https://openalex.org/W2065875833","https://openalex.org/W2084509516","https://openalex.org/W2096090700","https://openalex.org/W2106033751","https://openalex.org/W2107030642","https://openalex.org/W2109149988","https://openalex.org/W2116040950","https://openalex.org/W2118246710","https://openalex.org/W2127412835","https://openalex.org/W2133744395","https://openalex.org/W2135056195","https://openalex.org/W2143516773","https://openalex.org/W2169961966","https://openalex.org/W2219978888","https://openalex.org/W2578782924","https://openalex.org/W6633658626","https://openalex.org/W6679990451","https://openalex.org/W6680210282","https://openalex.org/W6732379946"],"related_works":["https://openalex.org/W2118381968","https://openalex.org/W2373659438","https://openalex.org/W2392905701","https://openalex.org/W4313052709","https://openalex.org/W2986132491","https://openalex.org/W1879755808","https://openalex.org/W2149987068","https://openalex.org/W2146487986","https://openalex.org/W2169551590","https://openalex.org/W2171653019"],"abstract_inverted_index":{"Accurate":[0],"segmentation":[1,28,130,139,163],"of":[2,60,121,127,160],"the":[3,51,58,65,96,103,119,122,128,137,151,171],"prostate":[4,9,24,27,66,147,172],"has":[5],"many":[6],"applications":[7],"in":[8,99],"cancer":[10],"diagnosis":[11],"and":[12,44],"therapy.":[13],"In":[14],"this":[15],"paper,":[16],"we":[17],"propose":[18],"a":[19,34,61,69,83,114,155],"\"Supervoxel\"":[20],"based":[21,117],"method":[22,91,164],"for":[23,170,175],"segmentation.":[25],"The":[26,54,72,125,142,162],"problem":[29],"is":[30,47,79,92,109],"considered":[31],"as":[32],"assigning":[33],"label":[35],"to":[36,49,64,68,81,94,101,112,136],"each":[37],"supervoxel.":[38],"An":[39],"energy":[40,97],"function":[41,98],"with":[42,134],"data":[43,55],"smoothness":[45,84],"terms":[46],"used":[48,80,93,111,167],"model":[50],"labeling":[52],"process.":[53],"term":[56],"estimates":[57],"likelihood":[59],"supervoxel":[62],"belongs":[63],"according":[67],"shape":[70],"feature.":[71],"geometric":[73],"relationship":[74],"between":[75],"two":[76],"neighboring":[77],"supervoxels":[78],"construct":[82],"term.":[85],"A":[86,105],"three-dimensional":[87],"(3D)":[88],"graph":[89,123],"cut":[90],"minimize":[95],"order":[100],"segment":[102],"prostate.":[104],"3D":[106],"level":[107],"set":[108],"then":[110],"get":[113],"smooth":[115],"surface":[116],"on":[118,145],"output":[120],"cut.":[124],"performance":[126],"proposed":[129,152],"algorithm":[131,153],"was":[132],"evaluated":[133],"respect":[135],"manual":[138],"ground":[140],"truth.":[141],"experimental":[143],"results":[144],"12":[146],"volumes":[148],"showed":[149],"that":[150],"yields":[154],"mean":[156],"Dice":[157],"similarity":[158],"coefficient":[159],"86.9%\u00b13.2%.":[161],"can":[165],"be":[166],"not":[168],"only":[169],"but":[173],"also":[174],"other":[176],"organs.":[177]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":3}],"updated_date":"2026-07-25T09:21:30.201066","created_date":"2025-10-10T00:00:00"}