{"id":"https://openalex.org/W1910109443","doi":"https://doi.org/10.1109/cvprw.2015.7301312","title":"Deep neural networks for anatomical brain segmentation","display_name":"Deep neural networks for anatomical brain segmentation","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1910109443","doi":"https://doi.org/10.1109/cvprw.2015.7301312","mag":"1910109443"},"language":"en","primary_location":{"id":"doi:10.1109/cvprw.2015.7301312","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw.2015.7301312","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","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/A5021132465","display_name":"Alexandre de Br\u00e9bisson","orcid":null},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Alexandre de Brebisson","raw_affiliation_strings":["Department of Mathematics, Imperial College London, London, UK","Department of Mathematics, Imperial College, London SW7\u00a02AZ, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"Department of Mathematics, Imperial College, London SW7\u00a02AZ, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010581004","display_name":"Giovanni Montana","orcid":"https://orcid.org/0000-0003-3942-3900"},"institutions":[{"id":"https://openalex.org/I1324925910","display_name":"St Thomas' Hospital","ror":"https://ror.org/054gk2851","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I1324925910","https://openalex.org/I200166805","https://openalex.org/I4210111135"]},{"id":"https://openalex.org/I183935753","display_name":"King's College London","ror":"https://ror.org/0220mzb33","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I183935753"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Giovanni Montana","raw_affiliation_strings":["Department of Biomedical Engineering, King's College London, London, UK","Department of Biomedical Engineering, King's College London, St Thomas' Hospital, SE1 7EH, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, King's College London, London, UK","institution_ids":["https://openalex.org/I183935753"]},{"raw_affiliation_string":"Department of Biomedical Engineering, King's College London, St Thomas' Hospital, SE1 7EH, UK","institution_ids":["https://openalex.org/I1324925910","https://openalex.org/I183935753"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":19.0958,"has_fulltext":false,"cited_by_count":337,"citation_normalized_percentile":{"value":0.9947004,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"20","last_page":"28"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T14510","display_name":"Medical Imaging and Analysis","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9987999796867371,"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/computer-science","display_name":"Computer science","score":0.7835389375686646},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7698526382446289},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.7295284271240234},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7226637005805969},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5976147651672363},{"id":"https://openalex.org/keywords/centroid","display_name":"Centroid","score":0.5599046349525452},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5517951846122742},{"id":"https://openalex.org/keywords/s\u00f8rensen\u2013dice-coefficient","display_name":"S\u00f8rensen\u2013Dice coefficient","score":0.535129725933075},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5347814559936523},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5122222304344177},{"id":"https://openalex.org/keywords/atlas","display_name":"Atlas (anatomy)","score":0.49743393063545227},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4516611695289612},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4200804829597473},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4140968918800354},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4065991938114166},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.11717480421066284},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.0744478702545166},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07235395908355713}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7835389375686646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7698526382446289},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.7295284271240234},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7226637005805969},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5976147651672363},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.5599046349525452},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5517951846122742},{"id":"https://openalex.org/C163892561","wikidata":"https://www.wikidata.org/wiki/Q2613728","display_name":"S\u00f8rensen\u2013Dice coefficient","level":4,"score":0.535129725933075},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5347814559936523},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5122222304344177},{"id":"https://openalex.org/C2776673561","wikidata":"https://www.wikidata.org/wiki/Q655357","display_name":"Atlas (anatomy)","level":2,"score":0.49743393063545227},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4516611695289612},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4200804829597473},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4140968918800354},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4065991938114166},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.11717480421066284},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0744478702545166},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07235395908355713},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvprw.2015.7301312","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw.2015.7301312","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","raw_type":"proceedings-article"},{"id":"pmh:oai:kclpure.kcl.ac.uk:publications/8682a334-4ce3-4a77-8989-f74360c1ccb8","is_oa":false,"landing_page_url":"https://kclpure.kcl.ac.uk/portal/en/publications/8682a334-4ce3-4a77-8989-f74360c1ccb8","pdf_url":null,"source":{"id":"https://openalex.org/S4306400216","display_name":"Research Portal (King's College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I183935753","host_organization_name":"King's College London","host_organization_lineage":["https://openalex.org/I183935753"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"De Br\u00e9bisson, A & Montana, G 2015, 'Deep neural networks for anatomical brain segmentation', IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp. 20-28. https://doi.org/10.1109/CVPRW.2015.7301312","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17","score":0.6000000238418579}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W22040386","https://openalex.org/W104184427","https://openalex.org/W1489942343","https://openalex.org/W1498436455","https://openalex.org/W1878430985","https://openalex.org/W1915761309","https://openalex.org/W2010587020","https://openalex.org/W2018662705","https://openalex.org/W2072128103","https://openalex.org/W2112796928","https://openalex.org/W2113651538","https://openalex.org/W2116462678","https://openalex.org/W2136478937","https://openalex.org/W2139427956","https://openalex.org/W2144803285","https://openalex.org/W2150534249","https://openalex.org/W2158778629","https://openalex.org/W2163605009","https://openalex.org/W2167510172","https://openalex.org/W2329786800","https://openalex.org/W2618530766","https://openalex.org/W4231109964","https://openalex.org/W6604254268","https://openalex.org/W6639333850","https://openalex.org/W6684191040","https://openalex.org/W6684372118"],"related_works":["https://openalex.org/W2381926679","https://openalex.org/W2007009951","https://openalex.org/W3027020613","https://openalex.org/W2082644203","https://openalex.org/W2314146950","https://openalex.org/W2011187995","https://openalex.org/W2373521488","https://openalex.org/W2016533837","https://openalex.org/W2324878645","https://openalex.org/W2803101231"],"abstract_inverted_index":{"We":[0,133],"present":[1],"a":[2,24,67],"novel":[3],"approach":[4],"to":[5,40,79,88,158],"automatically":[6],"segment":[7],"magnetic":[8],"resonance":[9],"(MR)":[10],"images":[11,129],"of":[12,37,47,58,101,124,130,147,163],"the":[13,38,48,56,80,102,111,115,131,145,156,160,164],"human":[14],"brain":[15,39,166],"into":[16],"anatomical":[17,43,161],"regions.":[18],"Our":[19],"methodology":[20],"is":[21,155],"based":[22],"on":[23,119],"deep":[25,168],"artificial":[26],"neural":[27,169],"network":[28,49],"that":[29],"assigns":[30],"each":[31],"voxel":[32,57],"in":[33],"an":[34],"MR":[35,103,128],"image":[36],"its":[41],"corresponding":[42],"region.":[44],"The":[45],"inputs":[46],"capture":[50,66],"information":[51],"at":[52],"different":[53],"scales":[54],"around":[55],"interest:":[59],"3D":[60],"and":[61,77],"orthogonal":[62,75],"2D":[63,74],"intensity":[64],"patches":[65,76],"local":[68],"spatial":[69,85],"context":[70],"while":[71],"downscaled":[72],"large":[73],"distances":[78],"regional":[81],"centroids":[82],"enforce":[83],"global":[84],"consistency.":[86],"Contrary":[87],"commonly":[89],"used":[90,110],"segmentation":[91,162],"methods,":[92],"our":[93,107,148,151,153],"technique":[94,154],"does":[95],"not":[96],"require":[97],"any":[98],"non-linear":[99],"registration":[100],"images.":[104],"To":[105,150],"benchmark":[106],"model,":[108],"we":[109],"dataset":[112],"provided":[113],"for":[114],"MICCAI":[116],"2012":[117],"challenge":[118],"multi-atlas":[120],"labelling,":[121],"which":[122],"consists":[123],"35":[125],"manually":[126],"segmented":[127],"brain.":[132],"obtained":[134],"competitive":[135],"results":[136],"(mean":[137],"dice":[138],"coefficient":[139],"0.725,":[140],"error":[141],"rate":[142],"0.163)":[143],"showing":[144],"potential":[146],"approach.":[149],"knowledge,":[152],"first":[157],"tackle":[159],"whole":[165],"using":[167],"networks.":[170]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":22},{"year":2022,"cited_by_count":36},{"year":2021,"cited_by_count":42},{"year":2020,"cited_by_count":52},{"year":2019,"cited_by_count":58},{"year":2018,"cited_by_count":44},{"year":2017,"cited_by_count":45},{"year":2016,"cited_by_count":12},{"year":2015,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}