Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Han-Gyeol Yeom"'
Publikováno v:
BMC Oral Health, Vol 24, Iss 1, Pp 1-9 (2024)
Abstract Background Radiolucencies found at the root apex in patients with cemento-osseous dysplasia (COD) may be mistaken for periapical cysts (PC) of endodontic origin. The purpose of this study was to examine the utility of quantitative texture an
Externí odkaz:
https://doaj.org/article/210b09f090664439912b36e9602c1467
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-8 (2023)
Abstract This study suggests a hybrid method based on ResNet50 and vision transformer (ViT) in an age estimation model. To this end, panoramic radiographs are used for learning by considering both local features and global information, which is impor
Externí odkaz:
https://doaj.org/article/b908198c18ca4123abcb0603878ba706
Autor:
Han-Gyeol Yeom, Kyung-Hoe Huh, Won-Jin Yi, Min-Suk Heo, Sam-Sun Lee, Soon-Chul Choi, Jo-Eun Kim
Publikováno v:
Head & Face Medicine, Vol 19, Iss 1, Pp 1-8 (2023)
Abstract The nasal cavity is an important landmark when considering implant insertion into the anterior region of the maxillary arch. The perforation of implants into the nasal cavity may cause complications, such as implant migration, inflammation,
Externí odkaz:
https://doaj.org/article/cfea36a25bdb4a97995ad6b36c98b505
Publikováno v:
BMC Oral Health, Vol 21, Iss 1, Pp 1-6 (2021)
Abstract Background The aim of this study was to report a rare case of nasopalatine duct cyst with sebaceous differentiation. Further, a systematic search of the literature was performed to identify studies reporting patients with intraosseous jaw cy
Externí odkaz:
https://doaj.org/article/2175159e748948109d17418332e76aa6
Autor:
WooSang Shin, Han-Gyeol Yeom, Ga Hyung Lee, Jong Pil Yun, Seung Hyun Jeong, Jong Hyun Lee, Hwi Kang Kim, Bong Chul Kim
Publikováno v:
BMC Oral Health, Vol 21, Iss 1, Pp 1-7 (2021)
Abstract Background Posteroanterior and lateral cephalogram have been widely used for evaluating the necessity of orthognathic surgery. The purpose of this study was to develop a deep learning network to automatically predict the need for orthodontic
Externí odkaz:
https://doaj.org/article/d071e29b844a4fad83981b75ebeb7dcf
Autor:
Jeong-Hun Yoo, Han-Gyeol Yeom, WooSang Shin, Jong Pil Yun, Jong Hyun Lee, Seung Hyun Jeong, Hun Jun Lim, Jun Lee, Bong Chul Kim
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
Abstract This paper proposes a convolutional neural network (CNN)-based deep learning model for predicting the difficulty of extracting a mandibular third molar using a panoramic radiographic image. The applied dataset includes a total of 1053 mandib
Externí odkaz:
https://doaj.org/article/ca8290bdccde45128660e9a4deb20ddd
Publikováno v:
Scientific Reports, Vol 10, Iss 1, Pp 1-5 (2020)
Abstract Facial photographs of the subjects are often used in the diagnosis process of orthognathic surgery. The aim of this study was to determine whether convolutional neural networks (CNNs) can judge soft tissue profiles requiring orthognathic sur
Externí odkaz:
https://doaj.org/article/60ac178f95e64fcb865e207ee1f34a63
Autor:
Han-Gyeol Yeom, Jung-Hoon Yoon
Publikováno v:
BMC Oral Health, Vol 20, Iss 1, Pp 1-6 (2020)
Abstract Background Concomitant cemento-osseous dysplasia (COD) and aneurysmal bone cyst (ABC) are rare in the head and neck region. In our search of the English language literature, we found only one case report describing the simultaneous occurrenc
Externí odkaz:
https://doaj.org/article/c4b108c937664c7b809f6fb66fd8d726
Autor:
Han-Gyeol Yeom, Jo-Eun Kim, Kyung-Hoe Huh, Won-Jin Yi, Min-Suk Heo, Sam-Sun Lee, Soon-Chul Choi
Publikováno v:
BMC Medical Imaging, Vol 20, Iss 1, Pp 1-8 (2020)
Abstract Background The purpose of this study was to analyze the correlation between spatial resolution and ball distortion rate of panoramic radiography and to elucidate the minimum criterion for ball distortion rate, which is very relevant to clini
Externí odkaz:
https://doaj.org/article/51f47699909547938296b5a5a98609e2
Publikováno v:
Diagnostics, Vol 11, Iss 4, p 591 (2021)
The aim of this study was to reveal cranio-spinal differences between skeletal classification using convolutional neural networks (CNNs). Transverse and longitudinal cephalometric images of 832 patients were used for training and testing of CNNs (365
Externí odkaz:
https://doaj.org/article/5273b33d547b40f6bfac1b9adb8acfc5