Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Eunseo Gwon"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Accurate lesion diagnosis through computed tomography (CT) and advances in laparoscopic or robotic surgeries have increased partial nephrectomy survival rates. However, accurately marking the kidney resection area through the laparoscope is
Externí odkaz:
https://doaj.org/article/ae75ae07273b4c618cc7640a08f62f4f
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
Abstract In children with mandibular hypoplasia, airway management is challenging. However, detailed cephalometric assessment data for this population are sparse. The aim of this study was to find risk factors for predicting difficult airways in chil
Externí odkaz:
https://doaj.org/article/31e4f1abe0084477a8a57fc99a242eb4
Autor:
Sangwook Lee, Taehun Kim, Dayeong Hong, Junhyeok Ock, Jaeyoung Kwon, Eunseo Gwon, Jinhee Kwon, Joon Beom Seo, Eun Jin Chae, Dong Hyun Yang, Choung-Soo Kim, Yoon Soo Kyung, Beom Seok Ko, Sehoon Choi, Ho-Seok Sa, Namkug Kim
Publikováno v:
대한영상의학회지, Vol 80, Iss 2, Pp 213-225 (2019)
Three-dimensional (3D) printing technology, with additive manufacturing, can aid in the production of various kinds of patient-specific medical devices and implants in medical fields, which cannot be covered by mass production systems for producing
Externí odkaz:
https://doaj.org/article/31aaaa9993054383bfbda3b84120be92
Publikováno v:
American Journal of Orthodontics and Dentofacial Orthopedics. 163:143-144
Publikováno v:
American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics. 162(2)
This study aimed to evaluate a 3-dimensional (3D) U-Net-based convolutional neural networks model for the fully automatic segmentation of regional pharyngeal volume of interests (VOIs) in cone-beam computed tomography scans to compare the accuracy of
Autor:
Dong-Ryul Kim, Kyung-A Kim, Eunseo Gwon, Seung-Hak Baek, Hyo-Won Ahn, Hyun-Joo Yoon, Namkug Kim, Su-Jung Kim
Publikováno v:
European journal of orthodontics. 44(1)
Summary Objectives The aim of the study was to evaluate the accuracy of a cascaded two-stage convolutional neural network (CNN) model in detecting upper airway (UA) soft tissue landmarks in comparison with the skeletal landmarks on the lateral cephal
Autor:
Joon Beom Seo, Eun Jin Chae, Se Hoon Choi, Yoon Soo Kyung, Sang-wook Lee, Taehun Kim, Junhyeok Ock, Jinhee Kwon, Eunseo Gwon, Beom Seok Ko, Namkug Kim, Ho-Seok Sa, Dong Hyun Yang, Jaeyoung Kwon, Choung-Soo Kim, Dayeong Hong
Publikováno v:
대한영상의학회지, Vol 80, Iss 2, Pp 213-225 (2019)
Three-dimensional (3D) printing technology, with additive manufacturing, can aid in the production of various kinds of patient-specific medical devices and implants in medical fields, which cannot be covered by mass production systems for producing c
Publikováno v:
Scientific Reports
Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
Scientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
In children with mandibular hypoplasia, airway management is challenging. However, detailed cephalometric assessment data for this population are sparse. The aim of this study was to find risk factors for predicting difficult airways in children with
Publikováno v:
Scientific Reports, Vol 10, Iss 1, Pp 1-12 (2020)
Scientific Reports
Scientific Reports
Difficult tracheal intubation is the third most common respiratory-related adverse co-morbid episode and can lead to death or brain damage. Since difficult tracheal intubation is less frequent, trainees have fewer opportunities to perform difficult t
Publikováno v:
Value-based Radiology ISBN: 9783030315542
In this chapter, we present six case scenarios uncovering many common questions and issues that we may frequently face in the field of 3D printing in medicine where the radiologists will bring added value through their expertise. 3D printing in medic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5b78754f52519b258e09e15232790f72
https://doi.org/10.1007/174_2019_207
https://doi.org/10.1007/174_2019_207