Skip to main content

Kyu Sung Choi

Seoul National University · 医学

研究室紹介

Professor Kyu Sung Choi's research lab specializes in radiogenomics and medical image analysis, focusing on leveraging advanced deep learning and quantitative MRI techniques to predict molecular and clinical outcomes in neurological disorders. The lab investigates glioma classification through perfusion MRI and glymphatic system function in neuroinflammatory diseases like multiple sclerosis and neuromyelitis optica spectrum disorder. A key focus is developing interpretable AI models that enhance diagnostic reliability and reproducibility in neuroimaging, particularly for predicting MGMT methylation status, IDH genotype, and hematoma expansion. The lab also explores mental health prediction using multimodal data, including questionnaires and graph neural networks.

radiogenomicsdeep learningneuroimaginggliomasuicide risk prediction

Research Overview

Papers
142
Total Citations
1,098
Papers (5y)
99
Primary Field
医学

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
99total
2022
2023
2024
2025
2026
Citations per year (5y)
440total
20222023202420252026

Selected Papers

15
1
Article|119 citations·2019
Prediction of IDH genotype in gliomas with dynamic susceptibility contrast perfusion MR imaging using an explainable recurrent neural network
Kyu Sung Choi, Seung Hong Choi, Bumseok Jeong
SJR Q1Neuro-OncologyOA

BACKGROUND: The aim of this study was to predict isocitrate dehydrogenase (IDH) genotypes of gliomas using an interpretable deep learning application for dynamic susceptibility contrast (DSC) perfusion MRI. METHODS: Four hundred sixty-three patients with gliomas who underwent preoperative MRI were enrolled in the study. All the patients had immunohistopathologic diagnoses of either IDH-wildtype or IDH-mutant gliomas. Tumor subregions were segmented using a convolutional neural network followed b

GeneticsMedicine
2
Article|43 citations·2022
Validation of MRI-Based Models to Predict MGMT Promoter Methylation in Gliomas: BraTS 2021 Radiogenomics Challenge
Byung-Hoon Kim, Hyeonhoon Lee, Kyu Sung Choi, Ju Gang Nam, Chul‐Kee Park, Sung‐Hye Park, Jin Wook Chung, Seung Hong Choi
SJR Q1CancersOA

O6-methylguanine-DNA methyl transferase (MGMT) methylation prediction models were developed using only small datasets without proper external validation and achieved good diagnostic performance, which seems to indicate a promising future for radiogenomics. However, the diagnostic performance was not reproducible for numerous research teams when using a larger dataset in the RSNA-MICCAI Brain Tumor Radiogenomic Classification 2021 challenge. To our knowledge, there has been no study regarding the

GeneticsMedicine
3
Article|38 citations·2022
Artificial Intelligence in Neuroimaging: Clinical Applications
Kyu Sung Choi, Leonard Sunwoo
SJR Q4Investigative Magnetic Resonance ImagingOA
Radiology, Nuclear Medicine and ImagingMedicine
4
Article|30 citations·2024
Comparative analysis of glymphatic system alterations in multiple sclerosis and neuromyelitis optica spectrum disorder using MRI indices from diffusion tensor imaging
Minchul Kim, Inpyeong Hwang, Jung‐Hyun Park, Jin Wook Chung, Sung Min Kim, Ji‐hoon Kim, Kyu Sung Choi
SJR Q1Human Brain MappingOA

OBJECTIVE: The glymphatic system is a glial-based perivascular network that promotes brain metabolic waste clearance. Glymphatic system dysfunction has been observed in both multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD), indicating the role of neuroinflammation in the glymphatic system. However, little is known about how the two diseases differently affect the human glymphatic system. The present study aims to evaluate the diffusion MRI-based measures of the glymphat

Cellular and Molecular NeuroscienceNeuroscience
5
Article|27 citations·2020
Improving the Reliability of Pharmacokinetic Parameters at Dynamic Contrast-enhanced MRI in Astrocytomas: A Deep Learning Approach
Kyu Sung Choi, Sung‐Hye You, Yoseob Han, Jong Chul Ye, Bumseok Jeong, Seung Hong Choi
SJR Q1Radiology

Background Pharmacokinetic (PK) parameters obtained from dynamic contrast agent-enhanced (DCE) MRI evaluates the microcirculation permeability of astrocytomas, but the unreliability from arterial input function (AIF) remains a challenge. Purpose To develop a deep learning model that improves the reliability of AIF for DCE MRI and to validate the reliability and diagnostic performance of PK parameters by using improved AIF in grading astrocytomas. Materials and Methods This retrospective study in

Radiology, Nuclear Medicine and ImagingMedicine
6
Article|24 citations·2024
Predicting hematoma expansion in acute spontaneous intracerebral hemorrhage: integrating clinical factors with a multitask deep learning model for non-contrast head CT
Hyochul Lee, Junhyeok Lee, Joon Hwan Jang, Inpyeong Hwang, Kyu Sung Choi, Jung Hyun Park, Jin Wook Chung, Seung Hong Choi
SJR Q1NeuroradiologyOA

PURPOSE: To predict hematoma growth in intracerebral hemorrhage patients by combining clinical findings with non-contrast CT imaging features analyzed through deep learning. METHODS: Three models were developed to predict hematoma expansion (HE) in 572 patients. We utilized multi-task learning for both hematoma segmentation and prediction of expansion: the Image-to-HE model processed hematoma slices, extracting features and computing a normalized DL score for HE prediction. The Clinical-to-HE mo

NeurologyMedicine
7
Article|24 citations·2021
Deep graph neural network-based prediction of acute suicidal ideation in young adults
Kyu Sung Choi, Sunghwan Kim, Byung-Hoon Kim, Hong Jin Jeon, Jong‐Hoon Kim, Joon Hwan Jang, Bumseok Jeong
SJR Q1Scientific ReportsOA

Precise remote evaluation of both suicide risk and psychiatric disorders is critical for suicide prevention as well as for psychiatric well-being. Using questionnaires is an alternative to labor-intensive diagnostic interviews in a large general population, but previous models for predicting suicide attempts suffered from low sensitivity. We developed and validated a deep graph neural network model that increased the prediction sensitivity of suicide risk in young adults (n = 17,482 for training

Clinical PsychologyPsychology
8
Article|23 citations·2023
Added prognostic value of 3D deep learning-derived features from preoperative MRI for adult-type diffuse gliomas
Jung Oh Lee, Sung Soo Ahn, Kyu Sung Choi, Junhyeok Lee, Joon Hwan Jang, Jung Hyun Park, Inpyeong Hwang, Chul‐Kee Park, Sung‐Hye Park, Jin Wook Chung, Seung Hong Choi
SJR Q1Neuro-OncologyOA

BACKGROUND: To investigate the prognostic value of spatial features from whole-brain MRI using a three-dimensional (3D) convolutional neural network for adult-type diffuse gliomas. METHODS: In a retrospective, multicenter study, 1925 diffuse glioma patients were enrolled from 5 datasets: SNUH (n = 708), UPenn (n = 425), UCSF (n = 500), TCGA (n = 160), and Severance (n = 132). The SNUH and Severance datasets served as external test sets. Precontrast and postcontrast 3D T1-weighted, T2-weighted, a

GeneticsMedicine
9
Article|20 citations·2015
Evaluation of Perihilar Biliary Strictures: Does DWI Provide Additional Value to Conventional MRI?
Kyu Sung Choi, Jeong Min Lee, Ijin Joo, Joon Koo Han, Byung Ihn Choi
SJR Q1American Journal of Roentgenology

OBJECTIVE: The purpose of this study is to evaluate whether DWI provides additional value to conventional MRI with MRCP (MRI-MRCP) in the characterization of perihilar biliary strictures and in the evaluation of the longitudinal extent of perihilar cholangiocarcinomas. MATERIALS AND METHODS: One hundred fourteen patients with perihilar strictures (81 malignant and 33 benign) underwent gadobutrol-enhanced MRI-MRCP and DWI using 10 b values (0-1000 s/mm(2)). Two readers independently reviewed a co

Pulmonary and Respiratory MedicineMedicine
10
Article|19 citations·2014
Feasibility and outcomes of laparoscopic enucleation for pancreatic neoplasms
Kyu Sung Choi, Jun Chul Chung, Hyung Chul Kım
SJR Q2Annals of Surgical Treatment and ResearchOA

LE is a safe and effective procedure, and should be considered as a treatment option for pancreatic lesions that do not involve the main pancratic duct and have an outgrowing aspect with small tumor bed.

OncologyMedicine
11
Article|17 citations·2015
Percutaneous Aspiration Embolectomy Using Guiding Catheter for the Superior Mesenteric Artery Embolism
Kyu Sung Choi, Ji Dae Kim, Hyo‐Cheol Kim, Sangil Min, Seung-Kee Min, Hwan Jun Jae, Jin Wook Chung
SJR Q1Korean Journal of RadiologyOA

Percutaneous aspiration embolectomy is a useful tool in recanalization of embolic occlusion of the SMA in select patients.

SurgeryMedicine
12
Article|14 citations·2016
Early Gastric Cancers: Is CT Surveillance Necessary after Curative Endoscopic Submucosal Resection for Cancers That Meet the Expanded Criteria?
Kyu Sung Choi, Se Hyung Kim, Sang Gyun Kim, Joon Koo Han
SJR Q1Radiology

Purpose To determine the yield of follow-up abdominopelvic computed tomography (CT) in detecting extragastric recurrence after curative endoscopic submucosal dissection (ESD) for early gastric cancers (EGCs) that meet the expanded criteria. Materials and Methods Institutional review board approval was obtained for this retrospective study, and the requirement to obtain informed consent was waived. Patients who underwent curative ESD for EGCs that met the expanded criteria between November 2005 a

Pulmonary and Respiratory MedicineMedicine
13
Article|11 citations·2016
Extremely Small Pseudoparamagnetic Iron Oxide Nanoparticle as a Novel Blood Pool T1 Magnetic Resonance Contrast Agent for 3 T Whole-Heart Coronary Angiography in Canines
Eun‐Ah Park, Whal Lee, Young So, Yun‐Sang Lee, Bong-sik Jeon, Kyu Sung Choi, Eung‐Gyu Kim, Wan-Jae Myeong
SJR Q1Investigative Radiology

OBJECTIVE: The aim of this study was to evaluate an extremely small pseudoparamagnetic iron oxide nanoparticle (ESPIO), KEG3, as a potential blood pool agent in 3 T coronary magnetic resonance angiography (MRA) in canine models and compare its efficacy to that of a gadolinium-based contrast agent. MATERIALS AND METHODS: Nine mongrel dogs were subjected to whole-heart coronary MRA in 2 separate sessions at 7-day intervals with a 3 T scanner using the FLASH sequence with either gadoterate meglumin

Radiology, Nuclear Medicine and ImagingMedicine
14
Article|10 citations·2016
Intestinal malrotation in patients with situs anomaly: Implication of the relative positions of the superior mesenteric artery and vein
Kyu Sung Choi, Young Hun Choi, Jung‐Eun Cheon, Woo Sun Kim, In One Kim
SJR Q1European Journal of Radiology
SurgeryMedicine
15
Article|9 citations·2025
Deep learning-based quantification of T2-FLAIR mismatch sign: extending IDH mutation prediction in adult-type diffuse lower-grade glioma
Young Hun Jeon, Kyu Sung Choi, Kyung Hoon Lee, Seong Yun Jeong, Ji Ye Lee, Taehyuk Ham, Inpyeong Hwang, Roh‐Eul Yoo, Koung Mi Kang, Tae Jin Yun, Seung Hong Choi, Ji‐hoon Kim
SJR Q1European RadiologyOA

OBJECTIVES: To investigate the predictive value of the quantitative T2-FLAIR mismatch ratio (qT2FM) with fully automated tumor segmentation in adult-type diffuse lower-grade gliomas (LGGs). MATERIALS AND METHODS: This retrospective study included 218 consecutive patients (mean age, 47 years ± 15 [SD]; 125 males) diagnosed with adult-type diffuse LGG. The cohort was classified into IDH wild-type (IDHwt), IDH-mutant with 1p/19q-codeletion (IDHmut-Codel), and IDH-mutant without 1p/19q-codeletion (I

GeneticsMedicine

Research Areas

Radiology, Nuclear Medicine and ImagingGeneticsComputer Vision and Pattern RecognitionNeurologyCellular and Molecular NeuroscienceArtificial Intelligence

Kyu Sung Choiの研究をNubintでさらに深く

この研究室の論文をアプリで開き、AIと共に読み、要約し、引用しましょう。