{"id":"https://openalex.org/W2433387316","doi":"https://doi.org/10.1109/isbi.2016.7493347","title":"Supervised learning for brain MR segmentation via fusion of partially labeled multiple atlases","display_name":"Supervised learning for brain MR segmentation via fusion of partially labeled multiple atlases","publication_year":2016,"publication_date":"2016-04-01","ids":{"openalex":"https://openalex.org/W2433387316","doi":"https://doi.org/10.1109/isbi.2016.7493347","mag":"2433387316"},"language":"en","primary_location":{"id":"doi:10.1109/isbi.2016.7493347","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2016.7493347","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)","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/A5079798556","display_name":"Yan Deng","orcid":"https://orcid.org/0000-0002-0778-6144"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan Deng","raw_affiliation_strings":["Department of CISE, University of Florida, Gainesville, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of CISE, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059870257","display_name":"Anand Rangarajan","orcid":"https://orcid.org/0000-0001-8695-8436"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anand Rangarajan","raw_affiliation_strings":["Department of CISE, University of Florida, Gainesville, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of CISE, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016378470","display_name":"Baba C. Vemuri","orcid":"https://orcid.org/0000-0002-1400-5844"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Baba C. Vemuri","raw_affiliation_strings":["Department of CISE, University of Florida, Gainesville, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of CISE, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I33213144"],"apc_list":null,"apc_paid":null,"fwci":0.5032,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.75698075,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"633","last_page":"637"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9962999820709229,"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":0.9922999739646912,"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":0.8498241901397705},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7499690055847168},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7331475019454956},{"id":"https://openalex.org/keywords/atlas","display_name":"Atlas (anatomy)","score":0.6231105923652649},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6187117695808411},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.5741597414016724},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5036241412162781},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.45725932717323303}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8498241901397705},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7499690055847168},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7331475019454956},{"id":"https://openalex.org/C2776673561","wikidata":"https://www.wikidata.org/wiki/Q655357","display_name":"Atlas (anatomy)","level":2,"score":0.6231105923652649},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6187117695808411},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.5741597414016724},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5036241412162781},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.45725932717323303},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi.2016.7493347","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi.2016.7493347","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)","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":14,"referenced_works":["https://openalex.org/W66667701","https://openalex.org/W1140063081","https://openalex.org/W2031083838","https://openalex.org/W2040154627","https://openalex.org/W2045256826","https://openalex.org/W2069331971","https://openalex.org/W2102595307","https://openalex.org/W2113576511","https://openalex.org/W2124984765","https://openalex.org/W2128806031","https://openalex.org/W2143143237","https://openalex.org/W2148157540","https://openalex.org/W2148347694","https://openalex.org/W2162140684"],"related_works":["https://openalex.org/W1986655823","https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W3144569342","https://openalex.org/W3011384228","https://openalex.org/W2124969951","https://openalex.org/W2945274617","https://openalex.org/W4313052709","https://openalex.org/W4298131179","https://openalex.org/W2375430703"],"abstract_inverted_index":{"Fully":[0],"labeled":[1,33,65,114],"manual":[2],"segmentation":[3,36,62],"\u2014":[4],"a":[5,15,30,45,96,117],"cornerstone":[6],"of":[7,87,95,99],"neuro-anatomical":[8],"structure":[9],"segmentation,":[10],"is":[11],"known":[12],"to":[13,54,59,67,109],"be":[14],"tedious,":[16],"time-consuming":[17],"and":[18,49,58],"error-prone":[19],"task":[20],"even":[21,91],"for":[22],"trained":[23],"experts.":[24],"In":[25],"this":[26],"paper,":[27],"we":[28],"propose":[29],"novel":[31],"partially":[32,113],"multiple":[34,42],"atlas-based":[35],"algorithm":[37],"which":[38,79],"can":[39],"simultaneously":[40],"segment":[41],"structures":[43],"from":[44,63],"given":[46,112],"image.":[47],"Intra-":[48],"Inter-structural":[50],"constraints":[51],"are":[52],"imposed":[53],"preserve":[55],"spatial":[56],"relationships":[57],"propagate":[60],"the":[61,64,68,88,93,100,107,111],"regions":[66],"unlabeled":[69],"regions.":[70],"We":[71],"present":[72],"several":[73],"experiments":[74],"on":[75],"real":[76],"data":[77,90],"sets":[78],"show":[80],"that":[81],"our":[82,104],"approach":[83,105],"yields":[84],"accurate":[85],"segmentations":[86],"test":[89],"in":[92],"absence":[94],"large":[97],"percentage":[98],"atlas":[101],"labels.":[102],"Further,":[103],"has":[106],"ability":[108],"refine":[110],"atlases":[115],"via":[116],"supervised":[118],"learning":[119],"stage.":[120]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}