{"id":"https://openalex.org/W2566933120","doi":"https://doi.org/10.1145/3013971.3015778","title":"Gap connection of vascular branches by nonlinear least squares curve fitting algorithm","display_name":"Gap connection of vascular branches by nonlinear least squares curve fitting algorithm","publication_year":2016,"publication_date":"2016-12-03","ids":{"openalex":"https://openalex.org/W2566933120","doi":"https://doi.org/10.1145/3013971.3015778","mag":"2566933120"},"language":"en","primary_location":{"id":"doi:10.1145/3013971.3015778","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3013971.3015778","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th ACM SIGGRAPH Conference on Virtual-Reality Continuum and Its Applications in Industry - Volume 1","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/A5100661279","display_name":"Shifeng Zhao","orcid":"https://orcid.org/0000-0002-5037-169X"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shifeng Zhao","raw_affiliation_strings":["Beijing Normal University, Beijing, P.R.China"],"affiliations":[{"raw_affiliation_string":"Beijing Normal University, Beijing, P.R.China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041498197","display_name":"Xuesong Wang","orcid":"https://orcid.org/0000-0003-4910-4495"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuesong Wang","raw_affiliation_strings":["Beijing Normal University, Beijing, P.R.China"],"affiliations":[{"raw_affiliation_string":"Beijing Normal University, Beijing, P.R.China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002734812","display_name":"Yun Tian","orcid":"https://orcid.org/0000-0001-5574-2325"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Tian","raw_affiliation_strings":["Beijing Normal University, Beijing, P.R.China"],"affiliations":[{"raw_affiliation_string":"Beijing Normal University, Beijing, P.R.China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113749274","display_name":"Qingqiong Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingqiong Deng","raw_affiliation_strings":["Beijing Normal University, Beijing, P.R.China"],"affiliations":[{"raw_affiliation_string":"Beijing Normal University, Beijing, P.R.China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101833322","display_name":"Zhongke Wu","orcid":"https://orcid.org/0000-0003-3735-6476"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongke Wu","raw_affiliation_strings":["Beijing Normal University, Beijing, P.R.China"],"affiliations":[{"raw_affiliation_string":"Beijing Normal University, Beijing, P.R.China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021263022","display_name":"Mingquan Zhou","orcid":"https://orcid.org/0000-0002-6354-3948"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingquan Zhou","raw_affiliation_strings":["Beijing Normal University, Beijing, P.R.China"],"affiliations":[{"raw_affiliation_string":"Beijing Normal University, Beijing, P.R.China","institution_ids":["https://openalex.org/I25254941"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100661279"],"corresponding_institution_ids":["https://openalex.org/I25254941"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.14951248,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"345","last_page":"352"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9970999956130981,"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":0.9970999956130981,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9670000076293945,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9598000049591064,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/skeletonization","display_name":"Skeletonization","score":0.7723416090011597},{"id":"https://openalex.org/keywords/curve-fitting","display_name":"Curve fitting","score":0.7027608156204224},{"id":"https://openalex.org/keywords/classification-of-discontinuities","display_name":"Classification of discontinuities","score":0.6445140242576599},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5947678089141846},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5932447910308838},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5227296948432922},{"id":"https://openalex.org/keywords/smoothness","display_name":"Smoothness","score":0.4369680881500244},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36587387323379517},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.3312779664993286},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24230611324310303},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.1761544942855835}],"concepts":[{"id":"https://openalex.org/C23951316","wikidata":"https://www.wikidata.org/wiki/Q1984140","display_name":"Skeletonization","level":2,"score":0.7723416090011597},{"id":"https://openalex.org/C184389593","wikidata":"https://www.wikidata.org/wiki/Q603159","display_name":"Curve fitting","level":2,"score":0.7027608156204224},{"id":"https://openalex.org/C15627037","wikidata":"https://www.wikidata.org/wiki/Q541961","display_name":"Classification of discontinuities","level":2,"score":0.6445140242576599},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5947678089141846},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5932447910308838},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5227296948432922},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.4369680881500244},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36587387323379517},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.3312779664993286},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24230611324310303},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.1761544942855835},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3013971.3015778","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3013971.3015778","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th ACM SIGGRAPH Conference on Virtual-Reality Continuum and Its Applications in Industry - Volume 1","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2447711110","display_name":null,"funder_award_id":"NCET-13-0051","funder_id":"https://openalex.org/F4320334924","funder_display_name":"Program for New Century Excellent Talents in University"}],"funders":[{"id":"https://openalex.org/F4320334924","display_name":"Program for New Century Excellent Talents in University","ror":"https://ror.org/01mv9t934"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W26930887","https://openalex.org/W1584481253","https://openalex.org/W1968112999","https://openalex.org/W1972829195","https://openalex.org/W1986640343","https://openalex.org/W1988271714","https://openalex.org/W1989901937","https://openalex.org/W1990316402","https://openalex.org/W1994132205","https://openalex.org/W1997100715","https://openalex.org/W2017337998","https://openalex.org/W2027343742","https://openalex.org/W2032318411","https://openalex.org/W2048054280","https://openalex.org/W2050997451","https://openalex.org/W2076233414","https://openalex.org/W2082719482","https://openalex.org/W2092116933","https://openalex.org/W2106017906","https://openalex.org/W2122825283","https://openalex.org/W2151630878","https://openalex.org/W2164390922","https://openalex.org/W2168005337","https://openalex.org/W2170568150","https://openalex.org/W2369063752","https://openalex.org/W3105798037","https://openalex.org/W3150692130","https://openalex.org/W4205649593","https://openalex.org/W4254033929"],"related_works":["https://openalex.org/W2132416234","https://openalex.org/W2092783742","https://openalex.org/W2118553688","https://openalex.org/W2292955152","https://openalex.org/W2376130299","https://openalex.org/W2620696933","https://openalex.org/W4220907282","https://openalex.org/W2623093699","https://openalex.org/W1603323139","https://openalex.org/W41790368"],"abstract_inverted_index":{"The":[0,119,135],"integrity":[1],"of":[2,25,52,62,113,117,129,146],"vascular":[3,14,53,133,147],"structure":[4],"plays":[5],"an":[6,89],"important":[7],"role":[8],"in":[9,49,83,106,132],"medical":[10],"diagnosis.":[11],"Yet":[12],"segmented":[13,64],"usually":[15],"contain":[16],"undesirable":[17],"gaps.":[18],"In":[19],"order":[20],"to":[21,32,123],"recover":[22],"the":[23,26,34,37,60,63,109,114,125,139],"topology":[24],"real":[27],"vessel":[28],"network,":[29],"we":[30],"need":[31],"connect":[33],"gaps":[35,145],"between":[36],"closest":[38],"discontinuous":[39],"branches.":[40,85],"A":[41],"new":[42],"method":[43,121,140],"is":[44,57,77,88,141],"proposed":[45],"which":[46],"merges":[47],"discontinuities":[48,130],"three-dimensional(3D)":[50],"images":[51],"structures.":[54],"This":[55],"algorithm":[56,76],"based":[58],"on":[59],"skeletonization":[61],"network":[65],"followed":[66],"by":[67],"projection.":[68],"And":[69],"a":[70,97],"nonlinear":[71,98],"least":[72,99],"square":[73,100],"curve":[74,101],"fitting":[75,87,102,120,144],"then":[78],"applied":[79],"for":[80,92,143],"connection":[81],"disconnections":[82],"broken":[84],"Curve":[86],"essential":[90],"tool":[91],"analyzing":[93],"biological":[94],"data,":[95],"while":[96],"has":[103],"its":[104],"advantages":[105],"dealing":[107],"with":[108],"connectivity":[110],"and":[111],"smoothness":[112],"whole":[115],"piece":[116],"curves.":[118],"permits":[122],"merge":[124],"most":[126],"common":[127],"kinds":[128],"found":[131],"networks.":[134],"experimental":[136],"results":[137],"demonstrate":[138],"effective":[142],"structure.":[148]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}