{"id":"https://openalex.org/W4362603629","doi":"https://doi.org/10.1117/12.2645635","title":"Fully-automatic aortic valve landmarks detection with two-stage-based convolutional neural networks","display_name":"Fully-automatic aortic valve landmarks detection with two-stage-based convolutional neural networks","publication_year":2023,"publication_date":"2023-04-03","ids":{"openalex":"https://openalex.org/W4362603629","doi":"https://doi.org/10.1117/12.2645635"},"language":"en","primary_location":{"id":"doi:10.1117/12.2645635","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1117/12.2645635","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2023: Image Processing","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/A5036236491","display_name":"Qixiang Ma","orcid":"https://orcid.org/0000-0002-6351-3853"},"institutions":[{"id":"https://openalex.org/I4210105651","display_name":"Laboratoire Traitement du Signal et de l'Image","ror":"https://ror.org/01f1amm71","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I154526488","https://openalex.org/I154526488","https://openalex.org/I4210105651","https://openalex.org/I4210105774","https://openalex.org/I56067802"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Qixiang Ma","raw_affiliation_strings":["LTSI - Laboratoire Traitement du Signal et de l'Image (Campus Universitaire de Beaulieu - B\u00e2t 22 - 35042 Rennes - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LTSI - Laboratoire Traitement du Signal et de l'Image (Campus Universitaire de Beaulieu - B\u00e2t 22 - 35042 Rennes - France)","institution_ids":["https://openalex.org/I4210105651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006943184","display_name":"L\u00e9o Lemarchand","orcid":"https://orcid.org/0009-0000-1868-4410"},"institutions":[{"id":"https://openalex.org/I4210105651","display_name":"Laboratoire Traitement du Signal et de l'Image","ror":"https://ror.org/01f1amm71","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I154526488","https://openalex.org/I154526488","https://openalex.org/I4210105651","https://openalex.org/I4210105774","https://openalex.org/I56067802"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"L\u00e9o Lemarchand","raw_affiliation_strings":["LTSI - Laboratoire Traitement du Signal et de l'Image (Campus Universitaire de Beaulieu - B\u00e2t 22 - 35042 Rennes - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LTSI - Laboratoire Traitement du Signal et de l'Image (Campus Universitaire de Beaulieu - B\u00e2t 22 - 35042 Rennes - France)","institution_ids":["https://openalex.org/I4210105651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054731556","display_name":"Diane Chan-Sock-Line","orcid":null},"institutions":[{"id":"https://openalex.org/I4210105651","display_name":"Laboratoire Traitement du Signal et de l'Image","ror":"https://ror.org/01f1amm71","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I154526488","https://openalex.org/I154526488","https://openalex.org/I4210105651","https://openalex.org/I4210105774","https://openalex.org/I56067802"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Diane Chan-Sock-Line","raw_affiliation_strings":["LTSI - Laboratoire Traitement du Signal et de l'Image (Campus Universitaire de Beaulieu - B\u00e2t 22 - 35042 Rennes - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LTSI - Laboratoire Traitement du Signal et de l'Image (Campus Universitaire de Beaulieu - B\u00e2t 22 - 35042 Rennes - France)","institution_ids":["https://openalex.org/I4210105651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073568539","display_name":"Louis Rigal","orcid":null},"institutions":[{"id":"https://openalex.org/I4210105651","display_name":"Laboratoire Traitement du Signal et de l'Image","ror":"https://ror.org/01f1amm71","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I154526488","https://openalex.org/I154526488","https://openalex.org/I4210105651","https://openalex.org/I4210105774","https://openalex.org/I56067802"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Louis Rigal","raw_affiliation_strings":["LTSI - Laboratoire Traitement du Signal et de l'Image (Campus Universitaire de Beaulieu - B\u00e2t 22 - 35042 Rennes - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LTSI - Laboratoire Traitement du Signal et de l'Image (Campus Universitaire de Beaulieu - B\u00e2t 22 - 35042 Rennes - France)","institution_ids":["https://openalex.org/I4210105651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107466937","display_name":"Antoine Simon","orcid":null},"institutions":[{"id":"https://openalex.org/I4210105651","display_name":"Laboratoire Traitement du Signal et de l'Image","ror":"https://ror.org/01f1amm71","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I154526488","https://openalex.org/I154526488","https://openalex.org/I4210105651","https://openalex.org/I4210105774","https://openalex.org/I56067802"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Antoine Simon","raw_affiliation_strings":["LTSI - Laboratoire Traitement du Signal et de l'Image (Campus Universitaire de Beaulieu - B\u00e2t 22 - 35042 Rennes - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LTSI - Laboratoire Traitement du Signal et de l'Image (Campus Universitaire de Beaulieu - B\u00e2t 22 - 35042 Rennes - France)","institution_ids":["https://openalex.org/I4210105651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046736772","display_name":"Pascal Haigron","orcid":"https://orcid.org/0000-0003-3451-8193"},"institutions":[{"id":"https://openalex.org/I4210105651","display_name":"Laboratoire Traitement du Signal et de l'Image","ror":"https://ror.org/01f1amm71","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I154526488","https://openalex.org/I154526488","https://openalex.org/I4210105651","https://openalex.org/I4210105774","https://openalex.org/I56067802"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Pascal Haigron","raw_affiliation_strings":["LTSI - Laboratoire Traitement du Signal et de l'Image (Campus Universitaire de Beaulieu - B\u00e2t 22 - 35042 Rennes - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LTSI - Laboratoire Traitement du Signal et de l'Image (Campus Universitaire de Beaulieu - B\u00e2t 22 - 35042 Rennes - France)","institution_ids":["https://openalex.org/I4210105651"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5036236491"],"corresponding_institution_ids":["https://openalex.org/I4210105651"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08839574,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":null,"first_page":"13","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10172","display_name":"Cardiac Valve Diseases and Treatments","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10172","display_name":"Cardiac Valve Diseases and Treatments","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T11551","display_name":"Infective Endocarditis Diagnosis and Management","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/T10372","display_name":"Cardiac Imaging and Diagnostics","score":0.98580002784729,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6929152011871338},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6840721368789673},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6181730628013611},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.608601987361908},{"id":"https://openalex.org/keywords/landmark","display_name":"Landmark","score":0.4764145612716675},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4740069806575775},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46156424283981323},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4482828676700592},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.436631441116333},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41520053148269653}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6929152011871338},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6840721368789673},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6181730628013611},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.608601987361908},{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.4764145612716675},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4740069806575775},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46156424283981323},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4482828676700592},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.436631441116333},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41520053148269653},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1117/12.2645635","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1117/12.2645635","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2023: Image Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-04123263v1","is_oa":false,"landing_page_url":"https://hal.science/hal-04123263","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Medical Imaging 2023: Image Processing, Feb 2023, San Diego, United States. pp.124643K, ⟨10.1117/12.2645635⟩","raw_type":"Conference papers"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1150726894","https://openalex.org/W1522301498","https://openalex.org/W1854858598","https://openalex.org/W2122694177","https://openalex.org/W2502312327","https://openalex.org/W2606654769","https://openalex.org/W2784710428","https://openalex.org/W2797997321","https://openalex.org/W2798122215","https://openalex.org/W2883254254","https://openalex.org/W2910298507","https://openalex.org/W2919115771","https://openalex.org/W2921388585","https://openalex.org/W3169733297","https://openalex.org/W4295312788","https://openalex.org/W6627452844","https://openalex.org/W6631190155","https://openalex.org/W6638052181","https://openalex.org/W6697925102","https://openalex.org/W6724804524","https://openalex.org/W6736816831","https://openalex.org/W6747911595","https://openalex.org/W6750171631","https://openalex.org/W6750469568","https://openalex.org/W6753494528","https://openalex.org/W6766978945"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3167935049","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W2095030957","https://openalex.org/W2066827917"],"abstract_inverted_index":{"Aortic":[0,14],"valve":[1,145],"landmarks":[2,121],"detection":[3,29,106],"in":[4,122,131],"Computed":[5],"Tomography":[6],"(CT)":[7],"images":[8],"is":[9,55,188],"essential":[10],"for":[11,57],"planning":[12,34],"Transcatheter":[13],"Valve":[15],"Implantation":[16],"(TAVI)":[17],"and":[18,33,126,160],"establishing":[19],"predictive":[20],"factors":[21],"of":[22,79,119,157,163,167,180,185],"cardiac":[23,197],"conduction":[24],"disturbance.":[25],"The":[26,111,200],"fully":[27,50],"automatic":[28,51],"facilitates":[30],"the":[31,40,67,77,89,116,120,123,154,158,161,164,168],"measurement":[32],"while":[35],"reducing":[36],"interobserver":[37],"variability.":[38],"Although":[39],"emerged":[41],"Convolutional":[42],"Neural":[43],"Networks":[44],"(CNNs)":[45],"have":[46],"been":[47],"applied":[48],"to":[49,59,66,74,91,207],"landmark":[52],"detection,":[53],"it":[54],"challenging":[56],"CNNs":[58],"directly":[60],"process":[61,208],"large-scale":[62],"CT":[63,198],"volumes":[64],"due":[65],"limited":[68],"computational":[69],"resources.":[70],"Some":[71],"common":[72],"preprocessing":[73],"deal":[75],"with":[76],"limitation":[78],"resources,":[80],"such":[81],"as":[82],"down-sampling":[83],"or":[84,95,139],"center":[85],"cropping,":[86],"can":[87],"cause":[88],"volume":[90],"lose":[92],"detailed":[93],"features":[94],"global":[96,124],"information.":[97],"To":[98],"address":[99],"these":[100],"issues,":[101],"we":[102],"propose":[103],"a":[104],"two-stage":[105],"method":[107,113,201],"based":[108],"on":[109,136],"CNN.":[110],"proposed":[112],"initially":[114],"detects":[115],"approximate":[117],"positions":[118],"view":[125],"then":[127],"obtains":[128],"refined":[129],"results":[130],"local":[132],"regions,":[133],"without":[134],"overdependence":[135],"prior":[137],"knowledge":[138],"labor-intensive":[140],"preprocessing.":[141],"Eight":[142],"important":[143],"aortic":[144],"landmarks,":[146],"including":[147],"three":[148,151],"hinge":[149],"points,":[150,153],"commissure":[152],"middle":[155],"point":[156,162],"cusps,":[159],"lower":[165],"part":[166],"membranous":[169],"septum":[170],"are":[171],"automatically":[172],"detected":[173],"from":[174,190],"our":[175,191],"network.":[176],"An":[177],"overall":[178],"result":[179],"Mean":[181],"Radial":[182],"Error":[183],"(MRE)":[184],"2.23":[186],"mm":[187],"yielded":[189],"data":[192],"set":[193],"containing":[194],"150":[195],"individual":[196],"volumes.":[199],"takes":[202],"0.15":[203],"seconds":[204],"per":[205],"stage":[206],"one":[209],"volume,":[210],"showing":[211],"high":[212],"efficiency.":[213]},"counts_by_year":[],"updated_date":"2026-05-07T13:39:58.223016","created_date":"2025-10-10T00:00:00"}