{"id":"https://openalex.org/W4225674693","doi":"https://doi.org/10.1109/ismr48346.2021.9661529","title":"Deep Learning for Needle Detection in a Cannulation Simulator","display_name":"Deep Learning for Needle Detection in a Cannulation Simulator","publication_year":2021,"publication_date":"2021-11-17","ids":{"openalex":"https://openalex.org/W4225674693","doi":"https://doi.org/10.1109/ismr48346.2021.9661529"},"language":"en","primary_location":{"id":"doi:10.1109/ismr48346.2021.9661529","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ismr48346.2021.9661529","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Symposium on Medical Robotics (ISMR)","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/A5101653903","display_name":"Jianxin Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianxin Gao","raw_affiliation_strings":["Dept. of Electrical & Computer Engineering, Clemson University, Clemson"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electrical & Computer Engineering, Clemson University, Clemson","institution_ids":["https://openalex.org/I8078737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102074223","display_name":"Ju Lin","orcid":"https://orcid.org/0009-0006-7448-9752"},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ju Lin","raw_affiliation_strings":["Dept. of Electrical & Computer Engineering, Clemson University, Clemson"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electrical & Computer Engineering, Clemson University, Clemson","institution_ids":["https://openalex.org/I8078737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013315455","display_name":"Irfan Kil","orcid":"https://orcid.org/0000-0002-8063-5772"},"institutions":[{"id":"https://openalex.org/I4210155970","display_name":"Applied Medical Resources (United States)","ror":"https://ror.org/04habne08","country_code":"US","type":"company","lineage":["https://openalex.org/I4210155970"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Irfan Kil","raw_affiliation_strings":["Applied Medical Resources Corporation, Rancho Santa Margarita"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Applied Medical Resources Corporation, Rancho Santa Margarita","institution_ids":["https://openalex.org/I4210155970"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026719183","display_name":"Ravikiran B. Singapogu","orcid":"https://orcid.org/0000-0001-9056-8465"},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ravikiran B. Singapogu","raw_affiliation_strings":["Dept. of Bioengineering, Clemson University, Clemson"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Bioengineering, Clemson University, Clemson","institution_ids":["https://openalex.org/I8078737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046707769","display_name":"Richard E. Groff","orcid":"https://orcid.org/0000-0001-6994-821X"},"institutions":[{"id":"https://openalex.org/I8078737","display_name":"Clemson University","ror":"https://ror.org/037s24f05","country_code":"US","type":"education","lineage":["https://openalex.org/I8078737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Richard E. Groff","raw_affiliation_strings":["Dept. of Electrical & Computer Engineering, Clemson University, Clemson"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electrical & Computer Engineering, Clemson University, Clemson","institution_ids":["https://openalex.org/I8078737"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.34990266,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"25","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10641","display_name":"Central Venous Catheters and Hemodialysis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/3604","display_name":"Emergency Medical Services"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10641","display_name":"Central Venous Catheters and Hemodialysis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/3604","display_name":"Emergency Medical Services"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T14189","display_name":"Intravenous Infusion Technology and Safety","score":0.9617000222206116,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9459999799728394,"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":0.7486964464187622},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6838713884353638},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.645276665687561},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49665433168411255},{"id":"https://openalex.org/keywords/arteriovenous-fistula","display_name":"Arteriovenous fistula","score":0.4460764229297638},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.428190678358078},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.41491252183914185},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3540462851524353},{"id":"https://openalex.org/keywords/surgery","display_name":"Surgery","score":0.27164891362190247},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.19960707426071167}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7486964464187622},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6838713884353638},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.645276665687561},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49665433168411255},{"id":"https://openalex.org/C2779063477","wikidata":"https://www.wikidata.org/wiki/Q707837","display_name":"Arteriovenous fistula","level":2,"score":0.4460764229297638},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.428190678358078},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.41491252183914185},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3540462851524353},{"id":"https://openalex.org/C141071460","wikidata":"https://www.wikidata.org/wiki/Q40821","display_name":"Surgery","level":1,"score":0.27164891362190247},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.19960707426071167}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ismr48346.2021.9661529","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ismr48346.2021.9661529","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Symposium on Medical Robotics (ISMR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W2048128804","https://openalex.org/W2054416286","https://openalex.org/W2061723459","https://openalex.org/W2064675550","https://openalex.org/W2112796928","https://openalex.org/W2131146703","https://openalex.org/W2155696619","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2757455114","https://openalex.org/W2799782288","https://openalex.org/W2897350321","https://openalex.org/W2944350202","https://openalex.org/W2952003418","https://openalex.org/W2962902328","https://openalex.org/W2966160658","https://openalex.org/W2977540023","https://openalex.org/W3003697434","https://openalex.org/W3011608473","https://openalex.org/W3012497879","https://openalex.org/W3081833047","https://openalex.org/W3119944412","https://openalex.org/W3160450938","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6773765442"],"related_works":["https://openalex.org/W4225394202","https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W3032952384","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Cannulation":[0],"for":[1,20,71,169,174,187,205],"hemodialysis":[2],"is":[3,31,80,201],"the":[4,21,33,36,39,77,85,146,153,162,190,194],"act":[5],"of":[6,23,35,38,90,121,134],"inserting":[7],"a":[8,11,125,202,210],"needle":[9,78,207],"into":[10],"surgically":[12],"created":[13],"vascular":[14,40],"access":[15,41],"(e.g.,":[16],"an":[17],"arteriovenous":[18],"fistula)":[19],"purpose":[22],"dialysis.":[24],"The":[25,141,177],"main":[26],"risk":[27],"associated":[28],"with":[29],"cannulation":[30,55,135,191,213],"infiltration,":[32],"puncture":[34],"wall":[37],"after":[42],"entry,":[43],"which":[44],"can":[45],"cause":[46],"medical":[47],"complications.":[48],"Simulator-based":[49],"training":[50],"allows":[51],"clinicians":[52],"to":[53,67],"gain":[54],"experience":[56],"without":[57],"putting":[58],"patients":[59],"at":[60,222],"risk.":[61],"In":[62],"this":[63,97],"paper,":[64],"we":[65],"propose":[66],"use":[68,188],"deep-learning-based":[69],"techniques":[70],"detecting,":[72],"based":[73,102],"on":[74,103,184],"video,":[75],"whether":[76],"tip":[79],"in":[81,96,181,189,209],"or":[82],"has":[83],"infiltrated":[84],"simulated":[86],"fistula.":[87],"Three":[88],"categories":[89],"deep":[91],"neural":[92,109,116],"networks":[93,110,117],"are":[94,220],"investigated":[95],"work:":[98],"modified":[99,170,175],"pre-trained":[100,163],"models":[101,165],"VGG-16":[104,171],"and":[105,113,124,139,152,172,193,218],"ResNet-50,":[106],"light":[107,147],"convolutional":[108,114,122],"(light":[111],"CNNs),":[112],"recurrent":[115],"(CRNNs).":[118],"CRNNs":[119],"consist":[120],"layers":[123],"long":[126],"short-term":[127],"memory":[128],"(LSTM)":[129],"layer.":[130],"A":[131],"data":[132,216],"set":[133],"experiments":[136],"was":[137,179,196],"collected":[138],"analyzed.":[140],"results":[142],"show":[143],"that":[144],"both":[145],"CNN":[148],"(test":[149,155,166],"accuracy:":[150,156],"0.983)":[151,157],"CRNN":[154,178],"achieve":[158],"better":[159],"performance":[160,195],"than":[161],"baseline":[164],"accuracy":[167],"0.968":[168],"0.971":[173],"ResNet-50).":[176],"implemented":[180],"real":[182],"time":[183],"commodity":[185],"hardware":[186],"simulator,":[192],"verified.":[197],"Deep-learning":[198],"video":[199],"analysis":[200],"viable":[203],"method":[204],"detecting":[206],"state":[208],"low":[211],"cost":[212],"simulator.":[214],"Our":[215],"sets":[217],"code":[219],"released":[221],"https://github.com/axin233/DL_for_Needle_Detection_Cannulation.":[223]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}