{"id":"https://openalex.org/W2283542761","doi":"https://doi.org/10.2312/vcbm.20151230","title":"A Statistical Method for Surface Detection","display_name":"A Statistical Method for Surface Detection","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2283542761","doi":"https://doi.org/10.2312/vcbm.20151230","mag":"2283542761"},"language":"en","primary_location":{"id":"pmh:oai:www.open-access.bcu.ac.uk:4343","is_oa":false,"landing_page_url":"http://www.open-access.bcu.ac.uk/4343/","pdf_url":null,"source":{"id":"https://openalex.org/S4306402654","display_name":"BCU Open Access Repository (Birmingham City University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I12870472","host_organization_name":"Birmingham City University","host_organization_lineage":["https://openalex.org/I12870472"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference or Workshop Item"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.2312/vcbm.20151230","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032661629","display_name":"S W J Smith","orcid":"https://orcid.org/0000-0001-9276-0354"},"institutions":[{"id":"https://openalex.org/I12870472","display_name":"Birmingham City University","ror":"https://ror.org/00t67pt25","country_code":"GB","type":"education","lineage":["https://openalex.org/I12870472"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Smith, Samuel","raw_affiliation_strings":["Birmingham City University, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Birmingham City University, United Kingdom","institution_ids":["https://openalex.org/I12870472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101498598","display_name":"Ian Williams","orcid":"https://orcid.org/0000-0002-0651-0963"},"institutions":[{"id":"https://openalex.org/I12870472","display_name":"Birmingham City University","ror":"https://ror.org/00t67pt25","country_code":"GB","type":"education","lineage":["https://openalex.org/I12870472"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Williams, Ian","raw_affiliation_strings":["Birmingham City University, United Kingdom"],"affiliations":[{"raw_affiliation_string":"Birmingham City University, United Kingdom","institution_ids":["https://openalex.org/I12870472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5032661629"],"corresponding_institution_ids":["https://openalex.org/I12870472"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"217","last_page":"217"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9901000261306763,"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":0.9865999817848206,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6571201682090759},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5981652736663818},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5860252380371094},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5330440402030945},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.529859721660614},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5242003202438354},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.5022537708282471},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.44762158393859863},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.4213634729385376},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.420831561088562},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3332558870315552},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23010507225990295},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13895249366760254}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6571201682090759},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5981652736663818},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5860252380371094},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5330440402030945},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.529859721660614},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5242003202438354},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.5022537708282471},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.44762158393859863},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.4213634729385376},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.420831561088562},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3332558870315552},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23010507225990295},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13895249366760254}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:www.open-access.bcu.ac.uk:4343","is_oa":false,"landing_page_url":"http://www.open-access.bcu.ac.uk/4343/","pdf_url":null,"source":{"id":"https://openalex.org/S4306402654","display_name":"BCU Open Access Repository (Birmingham City University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I12870472","host_organization_name":"Birmingham City University","host_organization_lineage":["https://openalex.org/I12870472"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference or Workshop Item"},{"id":"doi:10.2312/vcbm.20151230","is_oa":true,"landing_page_url":"https://doi.org/10.2312/vcbm.20151230","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"mag:2283542761","is_oa":false,"landing_page_url":"https://diglib.eg.org/handle/10.2312/vcbm20151230","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"Eurographics","raw_type":null}],"best_oa_location":{"id":"doi:10.2312/vcbm.20151230","is_oa":true,"landing_page_url":"https://doi.org/10.2312/vcbm.20151230","pdf_url":null,"source":{"id":"https://openalex.org/S7407052899","display_name":"Eurographics","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"score":0.7599999904632568,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2135270413","https://openalex.org/W2766309284","https://openalex.org/W1980795064","https://openalex.org/W2032910659","https://openalex.org/W2171172046","https://openalex.org/W1998515699","https://openalex.org/W2138164395","https://openalex.org/W2161404774","https://openalex.org/W1498984669","https://openalex.org/W2312957464","https://openalex.org/W2100864581","https://openalex.org/W2950411583","https://openalex.org/W1966411054","https://openalex.org/W3198984101","https://openalex.org/W2023058188","https://openalex.org/W2039366193","https://openalex.org/W2075375541","https://openalex.org/W1819391519","https://openalex.org/W2115544127","https://openalex.org/W2071536971"],"abstract_inverted_index":{"This":[0,290],"work":[1],"presents":[2],"a":[3,11,65,154,160,165,206,216,224,235,306,315,322],"new":[4],"method":[5,16,157,171,202,264,297],"for":[6,35],"3D":[7,20,44,262,271],"surface":[8,21,72,77,155,236,242,266,311],"detection":[9,22,78,156,267,278],"using":[10],"statistical":[12,166,176],"dual-region":[13,161],"filter.":[14],"The":[15,187],"improves":[17],"over":[18,260],"traditional":[19],"techniques":[23],"by":[24,132,295],"resolving":[25],"interfaces":[26],"between":[27,182,213,281],"different":[28,175],"stochastic":[29,119,251,284],"textures,":[30],"while":[31],"maintaining":[32],"the":[33,89,111,135,139,180,183,230,248,261,270,277,319,328,350,364],"accuracy":[34],"gradient":[36,83],"based":[37],"interfaces.":[38],"Segmentation":[39],"is":[40,64,68,211,219,232,244,292],"commonly":[41],"applied":[42],"to":[43,53,96,113,256,344],"image":[45,90,214],"formats":[46],"such":[47,121],"as":[48,122],"MRI":[49,107,360],"and":[50,58,74,108,221,268,305,327,336,354,359],"CT":[51,109,358],"data":[52,361],"aid":[54],"high":[55,99,207,287],"level":[56],"visualisation":[57],"anatomical":[59],"model":[60],"creation.":[61],"Often":[62,105],"segmentation":[63,243],"process":[66],"which":[67,178],"reliant":[69],"on":[70],"accurate":[71],"information":[73],"typically":[75],"gradient-based":[76,144],"methods":[79,84],"are":[80,94,103,116,190,342],"applied.":[81],"These":[82],"identify":[85],"sharp":[86],"changes":[87],"in":[88,247,276,309,356],"intensity":[91,129,136,288],"profile,":[92],"however":[93],"known":[95],"fail":[97],"when":[98,205],"levels":[100],"of":[101,118,209,227,250,265,279,283,321,349],"noise":[102,133],"present.":[104],"within":[106],"data,":[110],"regions":[112,140,215,282],"be":[114,367],"segmented":[115],"areas":[117],"texture,":[120],"soft":[123],"tissue":[124],"structures,":[125],"this":[126,170,201,239],"can":[127,366],"resemble":[128],"boundaries":[130],"corrupted":[131],"where":[134,223,363],"profile":[137],"across":[138],"remains":[141],"constant,":[142],"rendering":[143],"operators":[145],"less":[146],"effective.":[147],"To":[148],"overcome":[149],"these":[150],"issues,":[151],"we":[152,172],"present":[153,254],"that":[158,204],"employs":[159],"neighbourhood":[162,184],"mask,":[163],"alongside":[164],"comparison":[167],"test.":[168],"Within":[169],"assess":[173],"eight":[174],"tests":[177,188,231],"measure":[179],"similarity":[181,210,228],"mask":[185],"regions.":[186],"presented":[189],"mean":[191],"based,":[192,194],"variance":[193],"non-parametric":[195],"or":[196],"distribution":[197],"based.":[198],"Results":[199],"from":[200,229],"show":[203,257],"degree":[208,226],"found":[212,233],"non-surface":[217],"point":[218],"detected,":[220],"likewise":[222],"low":[225],"signifies":[234],"location.":[237],"Through":[238],"process,":[240],"improved":[241],"achieved":[245],"even":[246],"presence":[249],"texture.":[252],"We":[253,313],"results":[255],"significant":[258],"improvements":[259,365],"Canny":[263],"also":[269],"Steerable":[272],"filter":[273,352],"method,":[274],"notably":[275],"surfaces":[280,304],"texture":[285,324],"with":[286],"variance.":[289],"improvement":[291],"further":[293],"illustrated":[294],"our":[296],"achieving":[298],"fewer":[299],"missed":[300],"interfaces,":[301],"more":[302],"complete":[303],"measured":[307],"reduction":[308],"spurious":[310],"responses.":[312],"employ":[314],"Monte-Carlo":[316],"analysis,":[317],"involving":[318],"development":[320],"synthetic":[323],"interface":[325],"datasets":[326],"corresponding":[329],"ground":[330],"truth":[331],"solutions.":[332],"Receiver":[333],"Operator":[334],"Characteristic":[335],"Precision":[337],"Recall":[338],"quantitative":[339],"performance":[340],"measures":[341],"used":[343],"compare":[345],"against":[346],"existing":[347],"state":[348],"art":[351],"methods,":[353],"application":[355],"real":[357],"shows":[362],"found.":[368]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}