{"id":"https://openalex.org/W4405304883","doi":"https://doi.org/10.1109/sipaim62974.2024.10783618","title":"AI-based Automatic Segmentation of Sinonasal Cavity in Cone-Beam Computed Tomography","display_name":"AI-based Automatic Segmentation of Sinonasal Cavity in Cone-Beam Computed Tomography","publication_year":2024,"publication_date":"2024-11-13","ids":{"openalex":"https://openalex.org/W4405304883","doi":"https://doi.org/10.1109/sipaim62974.2024.10783618"},"language":"en","primary_location":{"id":"doi:10.1109/sipaim62974.2024.10783618","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sipaim62974.2024.10783618","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 20th International Symposium on Medical Information Processing and Analysis (SIPAIM)","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/A5021940887","display_name":"J. Illescas","orcid":null},"institutions":[{"id":"https://openalex.org/I238302431","display_name":"Galileo University","ror":"https://ror.org/04c3msc18","country_code":"GT","type":"education","lineage":["https://openalex.org/I238302431"]}],"countries":["GT"],"is_corresponding":true,"raw_author_name":"J. Illescas","raw_affiliation_strings":["Universidad Galileo,BiomedLab,Guatemala City,Guatemala"],"affiliations":[{"raw_affiliation_string":"Universidad Galileo,BiomedLab,Guatemala City,Guatemala","institution_ids":["https://openalex.org/I238302431"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054210797","display_name":"Mar\u00eda P\u00e9rez","orcid":"https://orcid.org/0000-0001-9628-2767"},"institutions":[{"id":"https://openalex.org/I238302431","display_name":"Galileo University","ror":"https://ror.org/04c3msc18","country_code":"GT","type":"education","lineage":["https://openalex.org/I238302431"]}],"countries":["GT"],"is_corresponding":false,"raw_author_name":"M. Perez","raw_affiliation_strings":["Universidad Galileo,BiomedLab,Guatemala City,Guatemala"],"affiliations":[{"raw_affiliation_string":"Universidad Galileo,BiomedLab,Guatemala City,Guatemala","institution_ids":["https://openalex.org/I238302431"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045879234","display_name":"Julio Fajardo","orcid":"https://orcid.org/0000-0003-4034-189X"},"institutions":[{"id":"https://openalex.org/I238302431","display_name":"Galileo University","ror":"https://ror.org/04c3msc18","country_code":"GT","type":"education","lineage":["https://openalex.org/I238302431"]}],"countries":["GT"],"is_corresponding":false,"raw_author_name":"J. Fajardo","raw_affiliation_strings":["Universidad Galileo,BiomedLab,Guatemala City,Guatemala"],"affiliations":[{"raw_affiliation_string":"Universidad Galileo,BiomedLab,Guatemala City,Guatemala","institution_ids":["https://openalex.org/I238302431"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031209768","display_name":"Adri\u00e1n Lara","orcid":"https://orcid.org/0000-0001-5130-6470"},"institutions":[{"id":"https://openalex.org/I238302431","display_name":"Galileo University","ror":"https://ror.org/04c3msc18","country_code":"GT","type":"education","lineage":["https://openalex.org/I238302431"]}],"countries":["GT"],"is_corresponding":false,"raw_author_name":"A. Lara","raw_affiliation_strings":["Universidad Galileo,BiomedLab,Guatemala City,Guatemala"],"affiliations":[{"raw_affiliation_string":"Universidad Galileo,BiomedLab,Guatemala City,Guatemala","institution_ids":["https://openalex.org/I238302431"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004348146","display_name":"Favio Reyna","orcid":"https://orcid.org/0000-0003-1184-5159"},"institutions":[{"id":"https://openalex.org/I4210130711","display_name":"Centro de Epilepsia y Neurocirug\u00eda Funcional","ror":"https://ror.org/036gb6b33","country_code":"GT","type":"healthcare","lineage":["https://openalex.org/I4210130711"]}],"countries":["GT"],"is_corresponding":false,"raw_author_name":"F. Reyna","raw_affiliation_strings":["DiagnostiX Integra Medical,Guatemala City,Guatemala"],"affiliations":[{"raw_affiliation_string":"DiagnostiX Integra Medical,Guatemala City,Guatemala","institution_ids":["https://openalex.org/I4210130711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5021940887"],"corresponding_institution_ids":["https://openalex.org/I238302431"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.43370569,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11812","display_name":"Nasal Surgery and Airway Studies","score":0.9904000163078308,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/T11812","display_name":"Nasal Surgery and Airway Studies","score":0.9904000163078308,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/T10984","display_name":"Sinusitis and nasal conditions","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/2733","display_name":"Otorhinolaryngology"},"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/T11669","display_name":"Head and Neck Surgical Oncology","score":0.9606999754905701,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/cone-beam-computed-tomography","display_name":"Cone beam computed tomography","score":0.6773939728736877},{"id":"https://openalex.org/keywords/computed-tomography","display_name":"Computed tomography","score":0.617605447769165},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6164238452911377},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5083765387535095},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5041776895523071},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5040658712387085},{"id":"https://openalex.org/keywords/tomography","display_name":"Tomography","score":0.4849872589111328},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.45029211044311523},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.34544503688812256},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.22707036137580872},{"id":"https://openalex.org/keywords/radiology","display_name":"Radiology","score":0.18613967299461365},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.13845109939575195}],"concepts":[{"id":"https://openalex.org/C2779813781","wikidata":"https://www.wikidata.org/wiki/Q1224951","display_name":"Cone beam computed tomography","level":3,"score":0.6773939728736877},{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.617605447769165},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6164238452911377},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5083765387535095},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5041776895523071},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5040658712387085},{"id":"https://openalex.org/C163716698","wikidata":"https://www.wikidata.org/wiki/Q841267","display_name":"Tomography","level":2,"score":0.4849872589111328},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.45029211044311523},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.34544503688812256},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.22707036137580872},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.18613967299461365},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.13845109939575195}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sipaim62974.2024.10783618","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sipaim62974.2024.10783618","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 20th International Symposium on Medical Information Processing and Analysis (SIPAIM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2199128562","https://openalex.org/W2979996602","https://openalex.org/W3132282445","https://openalex.org/W3164376303","https://openalex.org/W3164718072","https://openalex.org/W4220719690","https://openalex.org/W4255375128","https://openalex.org/W6610929275","https://openalex.org/W6639824700","https://openalex.org/W6855355347"],"related_works":["https://openalex.org/W2188736150","https://openalex.org/W3185410177","https://openalex.org/W2606458993","https://openalex.org/W148771971","https://openalex.org/W2560800164","https://openalex.org/W4213194177","https://openalex.org/W4293073787","https://openalex.org/W2768843469","https://openalex.org/W2614950993","https://openalex.org/W1522196789"],"abstract_inverted_index":{"The":[0,35,91],"evaluation":[1],"of":[2,52,98],"the":[3,53,84,111],"sinonasal":[4,54,85],"cavity":[5,55,86],"and":[6,15,49,66,107],"paranasal":[7],"sinuses":[8],"is":[9],"crucial":[10],"for":[11,27],"diagnosing":[12],"nasal":[13],"disturbances":[14],"tumors":[16],"through":[17],"Cone-Beam":[18],"Computed":[19],"Tomography":[20],"(CBCT).":[21],"This":[22,70],"technology":[23],"provides":[24],"3D":[25,57,88],"volumes":[26],"better":[28],"visualization,":[29],"helping":[30],"rapidly":[31,82],"diagnose":[32],"different":[33],"diseases.":[34],"recent":[36],"advancements":[37],"in":[38,56,87,113],"artificial":[39],"intelligence":[40],"methodologies":[41],"applied":[42],"to":[43,68,81],"these":[44],"medical":[45],"images":[46],"permit":[47],"rapid":[48],"accurate":[50],"segmentation":[51,112],"CBCT":[58,89],"studies,":[59],"even":[60],"when":[61],"noise":[62],"characteristics":[63],"are":[64],"unknown":[65],"difficult":[67],"eliminate.":[69],"study":[71],"proposes":[72],"an":[73],"efficient":[74],"AI-based":[75],"method":[76,92],"using":[77],"a":[78,96],"2D":[79],"U-Net":[80],"segment":[83],"studies.":[90],"was":[93],"validated":[94],"on":[95],"dataset":[97],"102":[99],"subjects,":[100],"demonstrating":[101],"high":[102,108],"accuracy":[103],"(about":[104],"99.3":[105],"%)":[106],"efficiency,":[109],"performing":[110],"under":[114],"20":[115],"seconds.":[116]},"counts_by_year":[],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}