Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Eugene Shumilov"'
Autor:
Kaan Orhan, Mamat Shamshiev, Matvey Ezhov, Alexander Plaksin, Aida Kurbanova, Gürkan Ünsal, Maxim Gusarev, Maria Golitsyna, Seçil Aksoy, Melis Mısırlı, Finn Rasmussen, Eugene Shumilov, Alex Sanders
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-9 (2022)
Abstract This study aims to generate and also validate an automatic detection algorithm for pharyngeal airway on CBCT data using an AI software (Diagnocat) which will procure a measurement method. The second aim is to validate the newly developed art
Externí odkaz:
https://doaj.org/article/d22357d2f18d49e6b39dfc3cb305be03
Autor:
Matvey Ezhov, Maxim Gusarev, Maria Golitsyna, Julian M. Yates, Evgeny Kushnerev, Dania Tamimi, Secil Aksoy, Eugene Shumilov, Alex Sanders, Kaan Orhan
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-16 (2021)
Abstract In this study, a novel AI system based on deep learning methods was evaluated to determine its real-time performance of CBCT imaging diagnosis of anatomical landmarks, pathologies, clinical effectiveness, and safety when used by dentists in
Externí odkaz:
https://doaj.org/article/b225240d1f0b411598955245409d2c54
Autor:
Sevda Kurt Bayrakdar, Kaan Orhan, Ibrahim Sevki Bayrakdar, Elif Bilgir, Matvey Ezhov, Maxim Gusarev, Eugene Shumilov
Publikováno v:
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-9 (2021)
Abstract Background The aim of this study was to evaluate the success of the artificial intelligence (AI) system in implant planning using three-dimensional cone-beam computed tomography (CBCT) images. Methods Seventy-five CBCT images were included i
Externí odkaz:
https://doaj.org/article/d2f5cd8264774c6a9bf7a13a104d0243
Autor:
Matvey Ezhov, Maxim Gusarev, Maria Golitsyna, Julian M. Yates, Evgeny Kushnerev, Dania Tamimi, Secil Aksoy, Eugene Shumilov, Alex Sanders, Kaan Orhan
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-1 (2021)
Externí odkaz:
https://doaj.org/article/405f268820d04347b4783d7a85071ce7
Autor:
Kaan, Orhan, Mamat, Shamshiev, Matvey, Ezhov, Alexander, Plaksin, Aida, Kurbanova, Gürkan, Ünsal, Maxim, Gusarev, Maria, Golitsyna, Seçil, Aksoy, Melis, Mısırlı, Finn, Rasmussen, Eugene, Shumilov, Alex, Sanders
This study aims to generate and also validate an automatic detection algorithm for pharyngeal airway on CBCT data using an AI software (Diagnocat) which will procure a measurement method. The second aim is to validate the newly developed artificial i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99fd0ea1ce886ac7e8b59d2994639a88
https://doi.org/10.21203/rs.3.rs-1137054/v1
https://doi.org/10.21203/rs.3.rs-1137054/v1
Autor:
Alex Sanders, Seçil Aksoy, Matvey Ezhov, Julian Yates, Eugene Shumilov, Dania Tamimi, Maxim Gusarev, Maria Golitsyna, Evgeny Kushnerev, Kaan Orhan
Cone-beam computed tomography (CBCT) in dental practice is becoming increasingly popular. However, the correct teeth identification, positioning and diagnosis based on CBCT can be tedious and challenging for the untrained eye. This is due to addition
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::319370ee1c185819d93db4c4d279f2bc
https://doi.org/10.21203/rs.3.rs-303329/v1
https://doi.org/10.21203/rs.3.rs-303329/v1
Autor:
Sevda Kurt Bayrakdar, Kaan Orhan, Ibrahim Sevki Bayrakdar, Elif Bilgir, Matvey Ezhov, Maxim Gusarev, Eugene Shumilov
Background: The aim of this study was to evaluate the success of the artificial intelligence (AI) system in implant planning using three-dimensional cone-beam computed tomography (CBCT) images.Methods: Seventy-five CBCT images were included in this s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fb1802985db941ab33c045a0b85b2592
https://doi.org/10.21203/rs.3.rs-286578/v1
https://doi.org/10.21203/rs.3.rs-286578/v1
Autor:
Ibrahim Sevki Bayrakdar, Matvey Ezhov, Eugene Shumilov, Kaan Orhan, Maxim Gusarev, Elif Bilgir, Sevda Kurt Bayrakdar
Publikováno v:
BMC Medical Imaging
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-9 (2021)
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-9 (2021)
Background The aim of this study was to evaluate the success of the artificial intelligence (AI) system in implant planning using three-dimensional cone-beam computed tomography (CBCT) images. Methods Seventy-five CBCT images were included in this st
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::828b0c8c21c0e0b545cc5a7d8564512a
https://pubmed.ncbi.nlm.nih.gov/34011314
https://pubmed.ncbi.nlm.nih.gov/34011314
Autor:
Kaan Orhan, Eugene Shumilov, Maxim Gusarev, Matvey Ezhov, Ibrahim Sevki Bayrakdar, Elif Bilgir
Publikováno v:
Journal of stomatology, oral and maxillofacial surgery. 122(4)
Purpose The aim of this study was to evaluate the diagnostic performance of artificial intelligence (AI) application evaluating of the impacted third molar teeth in Cone-beam Computed Tomography (CBCT) images. Material and methods In total, 130 third
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5daae73ae8b0a1f7b475e847f3d69444
https://pubmed.ncbi.nlm.nih.gov/33346145
https://pubmed.ncbi.nlm.nih.gov/33346145
Autor:
Maxim Gusarev, Kaan Orhan, Alex Sanders, Seçil Aksoy, Eugene Shumilov, Matvey Ezhov, Julian Yates, Evgeny Kushnerev, Maria Golitsyna, Dania Tamimi
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-1 (2021)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6a0d1e50cd62abaf17ffcfb4602964e6
https://doaj.org/article/405f268820d04347b4783d7a85071ce7
https://doaj.org/article/405f268820d04347b4783d7a85071ce7