{"id":"https://openalex.org/W2119042463","doi":"https://doi.org/10.1109/cvprw.2008.4562994","title":"Geometric modeling of tubular structures","display_name":"Geometric modeling of tubular structures","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2119042463","doi":"https://doi.org/10.1109/cvprw.2008.4562994","mag":"2119042463"},"language":"en","primary_location":{"id":"doi:10.1109/cvprw.2008.4562994","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw.2008.4562994","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","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/A5002822715","display_name":"Mehmet Gulsun","orcid":null},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]},{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"M. Akif Gulsun","raw_affiliation_strings":["Siemens AG Corporate Research and Development, Princeton, NJ, USA","Siemens Corp. Research, Princeton, NJ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Siemens AG Corporate Research and Development, Princeton, NJ, USA","institution_ids":["https://openalex.org/I4210137693"]},{"raw_affiliation_string":"Siemens Corp. Research, Princeton, NJ","institution_ids":["https://openalex.org/I20089843"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008529335","display_name":"H\u00fcseyin Tek","orcid":null},"institutions":[{"id":"https://openalex.org/I20089843","display_name":"Princeton University","ror":"https://ror.org/00hx57361","country_code":"US","type":"education","lineage":["https://openalex.org/I20089843"]},{"id":"https://openalex.org/I4210137693","display_name":"Siemens (United States)","ror":"https://ror.org/04axb7e79","country_code":"US","type":"company","lineage":["https://openalex.org/I1325886976","https://openalex.org/I4210137693"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huseyin Tek","raw_affiliation_strings":["Siemens AG Corporate Research and Development, Princeton, NJ, USA","Siemens Corp. Research, Princeton, NJ"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Siemens AG Corporate Research and Development, Princeton, NJ, USA","institution_ids":["https://openalex.org/I4210137693"]},{"raw_affiliation_string":"Siemens Corp. Research, Princeton, NJ","institution_ids":["https://openalex.org/I20089843"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.065,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.80251281,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"18","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","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"}},"topics":[{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","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"}},{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9832000136375427,"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/medial-axis","display_name":"Medial axis","score":0.6484776735305786},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5909783840179443},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.5822027325630188},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5759304165840149},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5126058459281921},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4862017035484314},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4825229346752167},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4528927206993103},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4339573383331299},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.43180859088897705},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42380964756011963},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39034509658813477},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25186097621917725},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.20377126336097717},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.14787334203720093},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.1405942738056183}],"concepts":[{"id":"https://openalex.org/C185877587","wikidata":"https://www.wikidata.org/wiki/Q1757407","display_name":"Medial axis","level":2,"score":0.6484776735305786},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5909783840179443},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.5822027325630188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5759304165840149},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5126058459281921},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4862017035484314},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4825229346752167},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4528927206993103},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4339573383331299},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.43180859088897705},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42380964756011963},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39034509658813477},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25186097621917725},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.20377126336097717},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.14787334203720093},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.1405942738056183},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvprw.2008.4562994","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw.2008.4562994","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.419.8826","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.419.8826","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://mplab.ucsd.edu/wp-content/uploads/CVPR2008/WorkShops/data/papers/045.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.5099999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W77022496","https://openalex.org/W1569930776","https://openalex.org/W1588596779","https://openalex.org/W1973965874","https://openalex.org/W2027647533","https://openalex.org/W2096987457","https://openalex.org/W2098158945","https://openalex.org/W2101817039","https://openalex.org/W2117740473","https://openalex.org/W2130384788","https://openalex.org/W2137948437","https://openalex.org/W2138905090","https://openalex.org/W2153392724","https://openalex.org/W2169528473","https://openalex.org/W6680132111"],"related_works":["https://openalex.org/W2907088218","https://openalex.org/W2051997380","https://openalex.org/W2541311741","https://openalex.org/W2269935213","https://openalex.org/W2057456086","https://openalex.org/W2568929922","https://openalex.org/W1522196789","https://openalex.org/W2116251909","https://openalex.org/W2112871239","https://openalex.org/W1984178488"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"present":[4],"a":[5,28,64,74,78],"method":[6,20,91],"for":[7],"extracting":[8],"center":[9,97],"axis":[10,98],"representations":[11],"of":[12,89,99,111],"tubular":[13,49,100],"shapes":[14,55,101],"obtained":[15,36],"from":[16,27,37,45,77,120],"medical":[17],"images.":[18],"The":[19,59,86],"extracts":[21],"centerlines":[22],"by":[23],"computing":[24],"minimum-cost":[25],"paths":[26],"graph":[29],"based":[30],"optimization":[31],"algorithm":[32,61],"which":[33,81,102],"minimizes":[34],"responses":[35],"multi-scale":[38],"medialness":[39],"filters.":[40],"These":[41],"filters":[42],"are":[43],"designed":[44],"the":[46,90,118],"assumption":[47],"that":[48],"structures,":[50],"in":[51,56],"general,":[52],"has":[53],"circular":[54],"cross-sectional":[57],"views.":[58],"proposed":[60],"can":[62,82],"produce":[63],"local":[65],"centerline":[66,75],"segment":[67],"between":[68],"two":[69],"points":[70],"as":[71,73],"well":[72],"tree":[76],"single":[79],"seed,":[80],"be":[83],"detected":[84],"automatically.":[85],"main":[87],"contribution":[88],"is":[92],"its":[93],"ability":[94],"to":[95,117],"extract":[96],"may":[103],"contain":[104],"boundary":[105],"noise,":[106],"holes,":[107],"gaps":[108],"and":[109],"attachment":[110],"nearby":[112],"structures":[113],"or":[114],"pathologies":[115],"due":[116],"errors":[119],"segmentation":[121],"algorithms.":[122]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
