{"id":"https://openalex.org/W2785781886","doi":"https://doi.org/10.1109/icip.2017.8296577","title":"Fully connected CRF with data-driven prior for multi-class brain tumor segmentation","display_name":"Fully connected CRF with data-driven prior for multi-class brain tumor segmentation","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2785781886","doi":"https://doi.org/10.1109/icip.2017.8296577","mag":"2785781886"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8296577","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296577","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 Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://discovery.dundee.ac.uk/files/20709842/ICIP_1584.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016921983","display_name":"Haocheng Shen","orcid":"https://orcid.org/0000-0001-6502-1177"},"institutions":[{"id":"https://openalex.org/I177639307","display_name":"University of Dundee","ror":"https://ror.org/03h2bxq36","country_code":"GB","type":"education","lineage":["https://openalex.org/I177639307"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Haocheng Shen","raw_affiliation_strings":["CVIP, University of Dundee, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CVIP, University of Dundee, UK","institution_ids":["https://openalex.org/I177639307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100461783","display_name":"Jianguo Zhang","orcid":"https://orcid.org/0000-0001-9317-0268"},"institutions":[{"id":"https://openalex.org/I177639307","display_name":"University of Dundee","ror":"https://ror.org/03h2bxq36","country_code":"GB","type":"education","lineage":["https://openalex.org/I177639307"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jianguo Zhang","raw_affiliation_strings":["CVIP, University of Dundee, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CVIP, University of Dundee, UK","institution_ids":["https://openalex.org/I177639307"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5494,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.71929591,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1727","last_page":"1731"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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/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"}}],"keywords":[{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.7496659159660339},{"id":"https://openalex.org/keywords/crfs","display_name":"CRFS","score":0.7342449426651001},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.691559374332428},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6751708984375},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6592541337013245},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6291677951812744},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5786427855491638},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5656169652938843},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5286151766777039},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5173327326774597},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.44715026021003723},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.42242273688316345},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39652928709983826}],"concepts":[{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.7496659159660339},{"id":"https://openalex.org/C2775953691","wikidata":"https://www.wikidata.org/wiki/Q5013874","display_name":"CRFS","level":3,"score":0.7342449426651001},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.691559374332428},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6751708984375},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6592541337013245},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6291677951812744},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5786427855491638},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5656169652938843},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5286151766777039},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5173327326774597},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.44715026021003723},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.42242273688316345},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39652928709983826},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icip.2017.8296577","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8296577","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 Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:discovery.dundee.ac.uk:openaire/66a2942b-2eac-4462-b19e-27d1c7a719ce","is_oa":true,"landing_page_url":"https://discovery.dundee.ac.uk/en/publications/66a2942b-2eac-4462-b19e-27d1c7a719ce","pdf_url":"https://discovery.dundee.ac.uk/files/20709842/ICIP_1584.pdf","source":{"id":"https://openalex.org/S4306400523","display_name":"Discovery Research Portal (University of Dundee)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I177639307","host_organization_name":"University of Dundee","host_organization_lineage":["https://openalex.org/I177639307"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Shen, H & Zhang, J 2018, Fully Connected Crf With Data-driven Prior for Multi-class Brain Tumor Segmentation. in 2017 IEEE International Conference on Image Processing (ICIP) : 17-20 Sept. 2017. IEEE Conference Proceedings, IEEE, pp. 1727-1731, The International Conference on Image Processing 2017, Beijing, China, 17/09/17. https://doi.org/10.1109/ICIP.2017.8296577","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:discovery.dundee.ac.uk:publications/66a2942b-2eac-4462-b19e-27d1c7a719ce","is_oa":false,"landing_page_url":"http://www.scopus.com/inward/record.url?scp=85045301362&partnerID=8YFLogxK","pdf_url":null,"source":{"id":"https://openalex.org/S4306400523","display_name":"Discovery Research Portal (University of Dundee)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I177639307","host_organization_name":"University of Dundee","host_organization_lineage":["https://openalex.org/I177639307"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":{"id":"pmh:oai:discovery.dundee.ac.uk:openaire/66a2942b-2eac-4462-b19e-27d1c7a719ce","is_oa":true,"landing_page_url":"https://discovery.dundee.ac.uk/en/publications/66a2942b-2eac-4462-b19e-27d1c7a719ce","pdf_url":"https://discovery.dundee.ac.uk/files/20709842/ICIP_1584.pdf","source":{"id":"https://openalex.org/S4306400523","display_name":"Discovery Research Portal (University of Dundee)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I177639307","host_organization_name":"University of Dundee","host_organization_lineage":["https://openalex.org/I177639307"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Shen, H & Zhang, J 2018, Fully Connected Crf With Data-driven Prior for Multi-class Brain Tumor Segmentation. in 2017 IEEE International Conference on Image Processing (ICIP) : 17-20 Sept. 2017. IEEE Conference Proceedings, IEEE, pp. 1727-1731, The International Conference on Image Processing 2017, Beijing, China, 17/09/17. https://doi.org/10.1109/ICIP.2017.8296577","raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G931371973","display_name":null,"funder_award_id":"61628212","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2785781886.pdf","grobid_xml":"https://content.openalex.org/works/W2785781886.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W32702003","https://openalex.org/W119341417","https://openalex.org/W1566328901","https://openalex.org/W1641498739","https://openalex.org/W1884191083","https://openalex.org/W1964772475","https://openalex.org/W2031223143","https://openalex.org/W2080927070","https://openalex.org/W2108082645","https://openalex.org/W2161236525","https://openalex.org/W2301358467","https://openalex.org/W2310992461","https://openalex.org/W2545985378","https://openalex.org/W2952793010","https://openalex.org/W6670646588","https://openalex.org/W6729085054"],"related_works":["https://openalex.org/W50079190","https://openalex.org/W2356597680","https://openalex.org/W182104056","https://openalex.org/W2111726165","https://openalex.org/W2011251309","https://openalex.org/W3108423214","https://openalex.org/W2796133761","https://openalex.org/W3088215229","https://openalex.org/W2511246383","https://openalex.org/W2184553228"],"abstract_inverted_index":{"Grid":[0],"conditional":[1],"random":[2],"fields":[3],"(CRFs)":[4],"are":[5,137],"widely":[6],"applied":[7],"in":[8,23,42,60,78],"both":[9],"natural":[10],"and":[11,39,92,113,134],"medical":[12],"image":[13,38],"segmentation":[14,59],"tasks.":[15],"However,":[16],"they":[17],"only":[18],"consider":[19],"the":[20,37,79,111,135,141],"label":[21],"coherence":[22],"neighborhood":[24],"pixels":[25,77],"or":[26],"regions,":[27],"which":[28],"limits":[29],"their":[30],"ability":[31],"to":[32,86,140],"model":[33,68,97],"long-range":[34],"connections":[35],"within":[36],"generally":[40],"results":[41,136],"excessive":[43],"smoothing":[44],"of":[45,76,90,103,116,127],"tumor":[46,58,91,104,129],"boundaries.":[47],"In":[48],"this":[49],"paper,":[50],"we":[51],"present":[52],"a":[53,83,95],"novel":[54],"method":[55],"for":[56],"brain":[57],"MR":[61],"images":[62],"based":[63],"on":[64,73,110],"fully-connected":[65],"CRF":[66],"(FC-CRF)":[67],"that":[69],"establishes":[70],"pairwise":[71],"potentials":[72],"all":[74],"pairs":[75],"images.":[80],"We":[81],"employ":[82],"hierarchical":[84],"approach":[85],"differentiate":[87],"different":[88],"structures":[89],"further":[93],"formulate":[94],"FC-CRF":[96],"with":[98],"learned":[99],"data-driven":[100],"prior":[101],"knowledge":[102],"core.":[105],"The":[106,125],"methods":[107],"were":[108],"evaluated":[109],"testing":[112],"leaderboard":[114],"set":[115],"Brain":[117],"Tumor":[118],"Image":[119],"Segmentation":[120],"Benchmark":[121],"(BRATS)":[122],"2013":[123],"challenge.":[124],"precision":[126],"segmented":[128],"boundaries":[130],"is":[131],"improved":[132],"significantly":[133],"competitive":[138],"compared":[139],"start-of-the-arts.":[142]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}