{"id":"https://openalex.org/W2900670549","doi":"https://doi.org/10.1142/s0218001419540259","title":"A GPU-Based Automatic Approach for Guide Wire Tracking in Fluoroscopic Sequences","display_name":"A GPU-Based Automatic Approach for Guide Wire Tracking in Fluoroscopic Sequences","publication_year":2018,"publication_date":"2018-11-12","ids":{"openalex":"https://openalex.org/W2900670549","doi":"https://doi.org/10.1142/s0218001419540259","mag":"2900670549"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001419540259","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001419540259","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-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/A5100420337","display_name":"Ken Chen","orcid":"https://orcid.org/0000-0002-4519-9362"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]},{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ken Chen","raw_affiliation_strings":["Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, China","Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Xili University Town, Xueyuan Road No. 1068, Shenzhen, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen College of Advanced Technology, University of Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210145761","https://openalex.org/I4210165038"]},{"raw_affiliation_string":"Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Xili University Town, Xueyuan Road No. 1068, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038433416","display_name":"Cheng Wang","orcid":"https://orcid.org/0000-0002-2290-4452"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Wang","raw_affiliation_strings":["Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210145761","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086187557","display_name":"Yaoqin Xie","orcid":"https://orcid.org/0000-0002-1412-2354"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaoqin Xie","raw_affiliation_strings":["Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210145761","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046902140","display_name":"Shoujun Zhou","orcid":"https://orcid.org/0000-0003-3232-6796"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shoujun Zhou","raw_affiliation_strings":["Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210145761","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100420337"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I3131625388","https://openalex.org/I4210145761","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.2089,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.56492676,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":95},"biblio":{"volume":"33","issue":"08","first_page":"1954025","last_page":"1954025"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9984999895095825,"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":0.9984999895095825,"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9976999759674072,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9972000122070312,"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":0.8066002726554871},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.6941965818405151},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6864999532699585},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6635367274284363},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5315238237380981},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.5027725696563721},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4830116033554077},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.41236284375190735}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8066002726554871},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.6941965818405151},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6864999532699585},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6635367274284363},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5315238237380981},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.5027725696563721},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4830116033554077},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.41236284375190735},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001419540259","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001419540259","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.699999988079071,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"},{"id":"https://openalex.org/F4320322927","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1965957146","https://openalex.org/W1995569250","https://openalex.org/W2034707285","https://openalex.org/W2049523102","https://openalex.org/W2067983060","https://openalex.org/W2075822095","https://openalex.org/W2110059349","https://openalex.org/W2129534965","https://openalex.org/W2132239611","https://openalex.org/W2132399803","https://openalex.org/W2145803225","https://openalex.org/W2147343920","https://openalex.org/W2154849962","https://openalex.org/W2794618406"],"related_works":["https://openalex.org/W4285411112","https://openalex.org/W1989791859","https://openalex.org/W2085033728","https://openalex.org/W2084086966","https://openalex.org/W2171299904","https://openalex.org/W2390829436","https://openalex.org/W1971289376","https://openalex.org/W2565094479","https://openalex.org/W2353744309","https://openalex.org/W2215635302"],"abstract_inverted_index":{"Guide":[0],"wire":[1,26,128,160,194],"tracking":[2,124,129,154,161],"in":[3,11,111,240],"fluoroscopic":[4,29,112,131,181],"images":[5,30],"has":[6],"done":[7],"a":[8,101,116,144,150,163,199],"significant":[9],"task":[10],"assisting":[12],"the":[13,24,28,33,46,69,158,214,225,229,237,251],"physicians":[14],"during":[15,45,58],"radiology-aided":[16],"interventions.":[17],"Many":[18],"groups":[19,49],"have":[20],"tried":[21],"to":[22,51,54,107,156,162,166],"detect":[23],"guide":[25,56,109,127,159,193],"from":[27,130],"based":[31],"on":[32,175],"image":[34],"properties.":[35],"The":[36],"main":[37],"challenge":[38],"is":[39,43,245],"that":[40],"manual":[41],"intervention":[42],"required":[44],"detection.":[47],"Other":[48],"try":[50],"introduce":[52],"localizers":[53],"track":[55,108],"wires":[57,110],"intervention,":[59],"which":[60],"requires":[61],"additional":[62],"hardware":[63],"equipment,":[64],"and":[65,93,104,119,137,148,186,205,217,220],"may":[66,82],"intervene":[67],"with":[68,250],"traditional":[70],"clinical":[71],"routines.":[72],"Machine":[73],"learning":[74],"methods":[75,81],"are":[76],"also":[77,149],"exploited.":[78],"Although":[79],"such":[80],"provide":[83],"accurate":[84],"tracking,":[85],"they":[86],"often":[87],"require":[88],"large":[89],"amount":[90],"of":[91,180,183,197,203,210],"data":[92,178],"training":[94],"time.":[95],"In":[96],"this":[97],"paper,":[98],"we":[99,142,233],"propose":[100,115,143],"GPU-based":[102,145],"fast":[103],"automatic":[105],"approach":[106],"sequences.":[113],"We":[114,170,189],"multi-scale":[117],"filtering":[118],"gradient":[120],"vector":[121],"field-based":[122],"real-time":[123,139],"method":[125,155,174],"for":[126,213,224,236],"images.":[132],"To":[133],"improve":[134,167],"calculation":[135,168,235],"efficiency":[136,244],"meet":[138],"application":[140],"requirement,":[141],"acceleration":[146,231],"scheme,":[147],"Bayesian":[151],"filter-like":[152],"motion":[153],"limit":[157],"smaller":[164],"range":[165],"efficiency.":[169],"test":[171,177],"our":[172],"proposed":[173,230],"two":[176],"sets":[179],"sequences":[182],"102":[184],"frames":[185],"72":[187],"frames.":[188],"achieve":[190],"an":[191,206],"average":[192],"detection":[195,201],"rate":[196,202],"96.7%,":[198],"false":[200],"0.0011%":[204],"error":[207],"distance":[208],"measure":[209],"0.83":[211],"pixels":[212],"first":[215,238],"sequence,":[216],"98.8%,":[218],"0.000069%":[219],"0.85":[221],"pixels,":[222],"respectively,":[223],"second":[226],"sequence.":[227],"With":[228],"method,":[232],"finish":[234],"sequence":[239],"nine":[241],"seconds,":[242],"thus,":[243],"enhanced":[246],"by":[247],"100":[248],"times":[249],"unaccelerated":[252],"algorithm.":[253]},"counts_by_year":[{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
