{"id":"https://openalex.org/W2333361544","doi":"https://doi.org/10.1117/12.2006811","title":"Hepatic vein segmentation using wavefront propagation and multiscale vessel enhancement","display_name":"Hepatic vein segmentation using wavefront propagation and multiscale vessel enhancement","publication_year":2013,"publication_date":"2013-03-13","ids":{"openalex":"https://openalex.org/W2333361544","doi":"https://doi.org/10.1117/12.2006811","mag":"2333361544"},"language":"en","primary_location":{"id":"doi:10.1117/12.2006811","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2006811","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"],"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/A5082214794","display_name":"Klaus Drechsler","orcid":"https://orcid.org/0000-0001-5423-6340"},"institutions":[{"id":"https://openalex.org/I3019423309","display_name":"Fraunhofer Institute for Computer Graphics Research","ror":"https://ror.org/04gmsar03","country_code":"DE","type":"facility","lineage":["https://openalex.org/I3019423309","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Klaus Drechsler","raw_affiliation_strings":["Fraunhofer-IGD (Germany)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer-IGD (Germany)","institution_ids":["https://openalex.org/I3019423309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032682986","display_name":"Cristina Oyarzun Laura","orcid":"https://orcid.org/0000-0002-8377-1374"},"institutions":[{"id":"https://openalex.org/I3019423309","display_name":"Fraunhofer Institute for Computer Graphics Research","ror":"https://ror.org/04gmsar03","country_code":"DE","type":"facility","lineage":["https://openalex.org/I3019423309","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Cristina Oyarzun Laura","raw_affiliation_strings":["Fraunhofer-IGD (Germany)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer-IGD (Germany)","institution_ids":["https://openalex.org/I3019423309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077049258","display_name":"Stefan Wesarg","orcid":null},"institutions":[{"id":"https://openalex.org/I3019423309","display_name":"Fraunhofer Institute for Computer Graphics Research","ror":"https://ror.org/04gmsar03","country_code":"DE","type":"facility","lineage":["https://openalex.org/I3019423309","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stefan Wesarg","raw_affiliation_strings":["Fraunhofer-IGD (Germany)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fraunhofer-IGD (Germany)","institution_ids":["https://openalex.org/I3019423309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I3019423309"],"apc_list":null,"apc_paid":null,"fwci":0.8312,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.77352546,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"8669","issue":null,"first_page":"86691A","last_page":"86691A"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9983999729156494,"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":0.9983999729156494,"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/T11438","display_name":"Retinal Imaging and Analysis","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9799000024795532,"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":0.7484054565429688},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6806690692901611},{"id":"https://openalex.org/keywords/hessian-matrix","display_name":"Hessian matrix","score":0.6586306691169739},{"id":"https://openalex.org/keywords/wavefront","display_name":"Wavefront","score":0.6578301787376404},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5525281429290771},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.536300778388977},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.5005865097045898},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.4998292922973633},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4681658446788788},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.45905646681785583},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.41315943002700806},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3554289638996124},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.2178497314453125},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.21520155668258667},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20679953694343567},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.144044429063797}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7484054565429688},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6806690692901611},{"id":"https://openalex.org/C203616005","wikidata":"https://www.wikidata.org/wiki/Q620495","display_name":"Hessian matrix","level":2,"score":0.6586306691169739},{"id":"https://openalex.org/C165699331","wikidata":"https://www.wikidata.org/wiki/Q461533","display_name":"Wavefront","level":2,"score":0.6578301787376404},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5525281429290771},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.536300778388977},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.5005865097045898},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.4998292922973633},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4681658446788788},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.45905646681785583},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.41315943002700806},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3554289638996124},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.2178497314453125},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.21520155668258667},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20679953694343567},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.144044429063797},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1117/12.2006811","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2006811","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":"pmh:oai:publica.fraunhofer.de:publica/381084","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/381084","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W176645828","https://openalex.org/W1877724968","https://openalex.org/W1974281449"],"related_works":["https://openalex.org/W4283017538","https://openalex.org/W1545275724","https://openalex.org/W1996936972","https://openalex.org/W2569979269","https://openalex.org/W3021699548","https://openalex.org/W2015677538","https://openalex.org/W4291718021","https://openalex.org/W2075777916","https://openalex.org/W2120338570","https://openalex.org/W2802707792"],"abstract_inverted_index":{"Modern":[0],"volumetric":[1,49,180],"imaging":[2],"techniques":[3],"such":[4,68],"as":[5,69,101,134],"CT":[6],"or":[7],"MRI,":[8],"aid":[9],"in":[10,37,48],"the":[11,21,110,147,166,172,198,211],"understanding":[12],"of":[13,29,45,130,169,210],"a":[14,61,79,87,102,152,163,179],"patient's":[15],"anatomy":[16],"and":[17,54,74,177,190,218,233,243],"pathologies.":[18],"Depending":[19],"on":[20,146,165,237],"medical":[22],"use":[23],"case,":[24],"various":[25],"anatomical":[26],"structures":[27,108,144],"are":[28,193],"interest.":[30],"Blood":[31],"vessels":[32,47],"play":[33],"an":[34,120],"important":[35],"role":[36],"several":[38,238],"applications,":[39],"e.g.":[40],"surgical":[41],"planning.":[42],"Manual":[43],"delineation":[44],"blood":[46],"images":[50],"is":[51,60,83,113,133,149,156,184,202,248],"error":[52],"prone":[53],"time":[55],"consuming.":[56],"Automated":[57],"vessel":[58,80,93,139,216],"segmentation":[59,81,112],"challenging":[62],"problem":[63],"due":[64],"to":[65,105,186],"acquisition-dependent":[66],"problems":[67],"noise,":[70],"contrast,":[71],"spatial":[72],"resolution,":[73],"artifacts.":[75],"In":[76],"this":[77,131],"paper,":[78],"method":[82,183,206],"presented":[84],"that":[85,158,171],"combines":[86],"wavefront":[88,153],"propagation":[89,154],"technique":[90,155],"with":[91],"Hessian-based":[92],"enhancement.":[94],"The":[95,116,128,204],"latter":[96],"has":[97],"proven":[98],"its":[99],"usefulness":[100],"preprocessing":[103],"step":[104],"detect":[106],"tubular":[107,143,199],"before":[109],"actual":[111],"carried":[114],"out.":[115],"former":[117],"allows":[118],"for":[119,142,215],"ordered":[121],"growing":[122],"process,":[123],"which":[124,192,225],"enables":[125],"topological":[126],"analysis.":[127],"contribution":[129],"work":[132],"follows.":[135],"1.":[136],"A":[137],"new":[138],"enhancement":[140,217],"filter":[141],"based":[145,236],"Laplacian":[148],"proposed,":[150],"2.":[151],"proposed":[157,185,205],"prevents":[159,219],"leaks":[160,220],"by":[161],"imposing":[162],"threshold":[164],"maximum":[167],"number":[168],"voxels":[170],"propagating":[173],"front":[174],"must":[175],"contain,":[176],"3.":[178],"hole":[181],"filling":[182],"filll":[187],"holes,":[188],"bays,":[189],"tunnels":[191],"caused":[194],"at":[195,222],"locations":[196],"where":[197],"structure":[200],"assumption":[201],"violated.":[203],"reduces":[207],"approximately":[208],"50%":[209],"necessary":[212],"eigenvalue":[213],"calculations":[214],"starting":[221],"small":[223],"spots,":[224],"usually":[226],"occur":[227],"using":[228],"standard":[229],"region":[230],"growing.":[231],"Qualitative":[232],"quantitative":[234],"evaluation":[235],"metrics":[239],"(statistical":[240],"measures,":[241],"dice":[242],"symmetric":[244],"average":[245],"surface":[246],"distance)":[247],"presented.":[249]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}