Kyung Tak Oh
Yonsei University · Medicine
About the Lab
Professor Kyung Tak Oh's research lab specializes in urological innovation, focusing on advancing diagnostic accuracy and treatment outcomes in urological diseases. Key research directions include optimizing prostate biopsy techniques for improved cancer detection, leveraging artificial intelligence—particularly convolutional neural networks—for real-time analysis of ureteroscopic images in kidney stone disease, and evaluating novel surgical therapies such as Aquablation and HoLEP for benign prostatic hyperplasia. The lab also pioneers transitional urology protocols to improve continuity of care for adolescent and young adult patients with urological conditions.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15Purpose: Several strategies of prostate biopsy (PBx) have been introduced to improve prostate cancer (PCa) detection rates. However, studies comparing cancer detection rates (CDRs) according to biopsy methods in real-world practice are scarce. This study aimed to investigate CDRs according to the biopsy methods for patients with prostate-specific antigen (PSA) <10.0 ng/mL. Materials and Methods: From 2006 to 2015, patients who underwent PBx were initially selected. All patients were categorized
Background and Objectives: Analysis of urine stone composition is one of the most important factors in urolithiasis treatment. This study investigated whether a convolutional neural network (CNN) can show decent results in predicting urinary stone composition even in single-use flexible ureterorenoscopic (fURS) images with relatively low resolution. Materials and Methods: This study retrospectively used surgical images from fURS lithotripsy performed by a single surgeon between January 2018 and
PURPOSE: This study aimed to compare the clinical outcomes of Aquablation and Holmium Laser Enucleation of the Prostate (HoLEP) for the treatment of benign prostatic hyperplasia (BPH), with emphasis on functional improvement, ejaculatory preservation, and perioperative safety. MATERIALS AND METHODS: We retrospectively analyzed data from January 2023 to March 2024, excluding patients with follow-up shorter than 3 months. Propensity score matching was performed using age, prostate volume, and preo
PURPOSE: In Korea, the field of transitional urology (TU) is in its nascent stages, with its introduction only beginning. This study aims to evaluate the existing state of TU prior to implementing a transition protocol, and to identify key areas of focus for the development of an effective transition protocol. METHODS: From June 1, 2021 to May 31, 2023, clinical data were retrospectively collected for patients who visited the adult urology or pediatric urology outpatient departments of this hosp
Remnant collateral veins of the internal spermatic vein (ISV) (Bahren type 3) are the most common cause of failure in ASV. In a few patients, an external spermatic vein merges with the ISV at a higher level (Bahren type 4) and is unidentifiable without venography.
In this paper, we propose a method to measure respiration rate by dividing the respiration related region in depth image using level set method. In the conventional method, the respiration related region was separated using the pre-defined region designated by the user. We separate the respiration related region using level set method combining shape prior knowledge. Median filter and clipping are performed as a preprocessing method for noise reduction in the depth image. As a feasibility test,
PURPOSE: We developed an innovative 2-stage procedure combining transurethral sphincterotomy (TURS) with artificial urinary sphincter (AUS) implantation to restore voiding in patients with refractory bladder emptying disorders. This proof-of-concept study evaluated its safety and efficacy. METHODS: We retrospectively reviewed clinical data from patients who underwent combined TURS and AUS implantation between April 7, 2021, and October 31, 2024. Eligible patients had neurogenic bladder with refr
본 논문은 깊이 카메라(Creative Senz3D)를 이용하여 호흡률을 측정하는 것에 대한 정확도와 영향을 미치는 요인들을 분석하였다. 영향 요인 분석에서는 깊이 카메라가 가지는 깊이 값에 대한 오차와 노이즈 그리고 주위 조도의 영향에 대하여 실험 연구를 진행하였다. 그 결과 깊이 카메라와 측정 대상의 거리가 증가함에 따라 깊이 값의 오차가 증가하였고 깊이 영상의 오른쪽은 실제 거리보다 깊이 값이 크게 측정되고 왼쪽은 실제 거리보다 깊이 값이 작게 측정되었다. 이에 따라 깊이 값이 영상의 영역에 따라 비대칭성을 가지고 있음을 알 수 있었다. 깊이 카메라와 측정 대상의 각도가 틀어짐에 따라서도 깊이 값의 차의 오차가 증가하였으며 깊이 카메라의 노이즈는 측정 거리가 멀어짐에 따라 점점 증가하였고 노이즈를 측정하는 윈도우의 크기가 증가함에 따라 감소하였다. 주위 조도는 깊이 값에 영향을 주지 않았다. 또한 실제 상황에서 사람을 대상으로 20회 호흡을 하게 하여 깊이 카메라를 이용해 호흡
You have accessJournal of UrologyCME1 Apr 2023PD34-07 CAN CONVOLUTIONAL NEURAL NETWORK BE APPLIED TO THE PREDICTION OF URINARY STONE COMPOSITION IN SINGLE-USE FLEXIBLE URETEROSCOPIC IMAGES? Kyung Tak Oh, Dae Young Jun, Jae Young Choi, Dae Chul Jung, and Joo Yong Lee Kyung Tak OhKyung Tak Oh More articles by this author , Dae Young JunDae Young Jun More articles by this author , Jae Young ChoiJae Young Choi More articles by this author , Dae Chul JungDae Chul Jung More articles by this author , a
In this paper, we propose a signal-based feature detection system for the early diagnosis of heart disease. The purpose of this study is to develop a compact healthcare system that extracts features from ECG signals. Therefore, the performance of the Tompkins algorithm, which is widely known as a signal-based feature detection algorithm, and the deep learning model of prior research are compared. In addition, by verifying the performance of the deep learning model by applying the Haar wavelet tr
The purpose of this study is to evaluate the impact of intermediate features on FER performance. To achieve this objective, intermediate features were extracted from the input images at specific layers (FM1~FM4) of the pre-trained network (Resnet-18). These extracted intermediate features and original images were used as inputs to the vision transformer (ViT), and the FER performance was compared. As a result, when using a single image as input, using intermediate features extracted from FM2 yie
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