{"id":"https://openalex.org/W4362487919","doi":"https://doi.org/10.1117/12.2655616","title":"Automatic chorda tympani segmentation with weakly supervised conditional adversarial networks","display_name":"Automatic chorda tympani segmentation with weakly supervised conditional adversarial networks","publication_year":2023,"publication_date":"2023-04-03","ids":{"openalex":"https://openalex.org/W4362487919","doi":"https://doi.org/10.1117/12.2655616"},"language":"en","primary_location":{"id":"doi:10.1117/12.2655616","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1117/12.2655616","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-Guided Procedures, Robotic Interventions, and Modeling","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/A5026711087","display_name":"Rueben Banalagay","orcid":null},"institutions":[{"id":"https://openalex.org/I200719446","display_name":"Vanderbilt University","ror":"https://ror.org/02vm5rt34","country_code":"US","type":"education","lineage":["https://openalex.org/I200719446"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Rueben A. Banalagay","raw_affiliation_strings":["Vanderbilt Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Vanderbilt Univ. (United States)","institution_ids":["https://openalex.org/I200719446"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000197945","display_name":"Jack H. Noble","orcid":"https://orcid.org/0000-0002-0973-505X"},"institutions":[{"id":"https://openalex.org/I200719446","display_name":"Vanderbilt University","ror":"https://ror.org/02vm5rt34","country_code":"US","type":"education","lineage":["https://openalex.org/I200719446"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jack H. Noble","raw_affiliation_strings":["Vanderbilt Univ. (United States)"],"affiliations":[{"raw_affiliation_string":"Vanderbilt Univ. (United States)","institution_ids":["https://openalex.org/I200719446"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5026711087"],"corresponding_institution_ids":["https://openalex.org/I200719446"],"apc_list":null,"apc_paid":null,"fwci":0.2033,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.3888715,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"29","last_page":"29"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10860","display_name":"Speech and Audio Processing","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10283","display_name":"Hearing Loss and Rehabilitation","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11698","display_name":"Underwater Acoustics Research","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7222422361373901},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7183355093002319},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.699073851108551},{"id":"https://openalex.org/keywords/chorda","display_name":"Chorda","score":0.5379121899604797},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4627523422241211},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4140138328075409},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4107299745082855},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.370347261428833}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7222422361373901},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7183355093002319},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.699073851108551},{"id":"https://openalex.org/C2775871351","wikidata":"https://www.wikidata.org/wiki/Q18378264","display_name":"Chorda","level":3,"score":0.5379121899604797},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4627523422241211},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4140138328075409},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4107299745082855},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.370347261428833},{"id":"https://openalex.org/C31903555","wikidata":"https://www.wikidata.org/wiki/Q1637030","display_name":"Food science","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C8868529","wikidata":"https://www.wikidata.org/wiki/Q124794","display_name":"Taste","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2655616","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1117/12.2655616","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-Guided Procedures, Robotic Interventions, and Modeling","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":15,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1972511383","https://openalex.org/W2034432063","https://openalex.org/W2048733914","https://openalex.org/W2065547022","https://openalex.org/W2074698924","https://openalex.org/W2120038148","https://openalex.org/W2142568997","https://openalex.org/W2146465394","https://openalex.org/W2522083379","https://openalex.org/W2813374562","https://openalex.org/W2962793481","https://openalex.org/W2965790690","https://openalex.org/W6631190155","https://openalex.org/W6643437503"],"related_works":["https://openalex.org/W2050952295","https://openalex.org/W2396437788","https://openalex.org/W2009911123","https://openalex.org/W2140839331","https://openalex.org/W2141666145","https://openalex.org/W2409278009","https://openalex.org/W3138919999","https://openalex.org/W2066525601","https://openalex.org/W4315434538","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Cochlear":[0],"Implants":[1],"(CI)":[2],"are":[3,47,195],"a":[4,36,124,137,142,161,173],"widely":[5],"successful":[6],"neural-prosthetic":[7],"device":[8],"for":[9,14,26,80,129,197],"improving":[10],"quality":[11],"of":[12,53,61,65,78,92,123,132,144,177,191],"life":[13],"individuals":[15],"experiencing":[16],"severe":[17],"to":[18,71,76,110,213],"profound":[19],"hearing":[20],"loss.":[21],"A":[22],"minimally":[23],"invasive":[24],"technique":[25],"inserting":[27],"the":[28,40,54,62,66,81,84,89,121,181],"CI":[29],"electrode,":[30],"percutaneous":[31],"cochlear":[32],"access,":[33],"typically":[34,207],"involves":[35,208],"surgical":[37,44],"trajectory":[38,205],"through":[39,153],"facial":[41,67],"recess.":[42,68],"Image-based":[43],"planning":[45,206],"techniques":[46],"heavily":[48],"reliant":[49],"on":[50],"accurate":[51],"segmentation":[52,131,165],"chorda":[55],"tympani":[56],"since":[57],"it":[58],"is":[59],"one":[60],"delineating":[63],"structures":[64],"Furthermore,":[69],"damage":[70],"this":[72,99,117,133],"structure":[73,100],"can":[74],"lead":[75],"loss":[77],"taste":[79],"patient.":[82],"However,":[83],"chorda\u2019s":[85],"thin":[86],"nature":[87],"and":[88,148],"surrounding":[90],"appearance":[91],"pneumatized":[93],"bone":[94],"pose":[95],"difficulties":[96],"when":[97],"segmenting":[98],"in":[101,113,164,180,200],"conventional":[102],"CT.":[103],"Our":[104,157],"previous":[105,169],"automatic":[106,130,154,170],"method":[107,171,185],"still":[108,186],"leads":[109],"unacceptable":[111],"inaccuracies":[112],"difficult":[114],"images.":[115],"In":[116],"work,":[118],"we":[119],"propose":[120],"use":[122,136,199],"conditional":[125],"generative":[126],"adversarial":[127],"network":[128,159],"structure.":[134],"We":[135],"weakly":[138],"supervised":[139],"approach,":[140],"leveraging":[141],"dataset":[143],"sixteen":[145],"hand-labelled":[146],"images":[147,151],"130":[149],"weakly-labelled":[150],"acquired":[152],"atlas-based":[155],"techniques.":[156],"resulting":[158],"displays":[160],"49%":[162],"increase":[163],"performance":[166],"over":[167],"our":[168,184],"with":[172],"mean":[174],"localization":[175,189],"error":[176,211],"0.49mm.":[178],"Even":[179],"worst":[182],"case,":[183],"provides":[187],"sub-millimeter":[188],"errors":[190],"0.82mm.":[192],"These":[193],"results":[194],"encouraging":[196],"potential":[198],"clinical":[201],"settings":[202],"as":[203],"safe":[204],"1":[209],"mm":[210],"margins":[212],"sensitive":[214],"structures.":[215]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}