Skip to main content

Hyoung Jin Kim

Seoul National University · 医学

研究室紹介

Professor Hyoung Jin Kim's research lab specializes in radiological and medical imaging innovation, focusing on advancing diagnostic accuracy and prognostic modeling in thoracic diseases. The lab integrates deep learning and radiomics with multidetector CT to improve the assessment of lung cancer, particularly adenocarcinoma and subsolid nodules, by extracting quantitative imaging features from preoperative scans. Research also emphasizes optimizing image reconstruction techniques to reduce variability and enhance diagnostic reliability, while exploring the clinical utility of advanced MRI sequences such as reduced field-of-view diffusion-weighted imaging. The lab's work bridges medical imaging, artificial intelligence, and clinical oncology to support personalized patient management.

radiomicslung cancerdeep learningchest CTmedical imaging

Research Overview

Papers
300
Total Citations
7,243
Papers (5y)
93
Primary Field
医学

Research Output Trend

Figures are computed from collected data and may differ slightly.

Publications per year (5y)
93total
2022
2023
2024
2025
2026
Citations per year (5y)
1,166total
20222023202420252026

Selected Papers

15
1
Review|561 citations·2020
Diagnostic Performance of CT and Reverse Transcriptase Polymerase Chain Reaction for Coronavirus Disease 2019: A Meta-Analysis
Hyungjin Kim, Hyunsook Hong, Soon Ho Yoon
SJR Q1RadiologyOA

Background Recent studies have suggested that chest CT scans could be used as a primary screening or diagnostic tool for coronavirus disease 2019 (COVID-19) in epidemic areas. Purpose To perform a meta-analysis to evaluate diagnostic performance measures, including predictive values of chest CT and initial reverse transcriptase polymerase chain reaction (RT-PCR). Materials and Methods Medline and Embase were searched from January 1, 2020, to April 3, 2020, for studies on COVID-19 that reported t

Infectious DiseasesMedicine
2
Article|257 citations·2018
Impact of viewer engagement on gift-giving in live video streaming
Eun Yu, ChanYong Jung, Hyungjin Kim, Jaemin Jung
SJR Q1Telematics and Informatics
Sociology and Political ScienceSocial Sciences
3
editorial|185 citations·2020
Outbreak of novel coronavirus (COVID-19): What is the role of radiologists?
Hyungjin Kim
SJR Q1European RadiologyOA
Radiology, Nuclear Medicine and ImagingMedicine
4
Article|148 citations·2016
Impact of Reconstruction Algorithms on CT Radiomic Features of Pulmonary Tumors: Analysis of Intra- and Inter-Reader Variability and Inter-Reconstruction Algorithm Variability
Hyungjin Kim, Chang Min Park, Myunghee Lee, Sang Joon Park, Yong Song, Jong Hyuk Lee, Eui Jin Hwang, Jin Mo Goo
SJR Q1PLoS ONEOA

PURPOSE: To identify the impact of reconstruction algorithms on CT radiomic features of pulmonary tumors and to reveal and compare the intra- and inter-reader and inter-reconstruction algorithm variability of each feature. METHODS: Forty-two patients (M:F = 19:23; mean age, 60.43±10.56 years) with 42 pulmonary tumors (22.56±8.51mm) underwent contrast-enhanced CT scans, which were reconstructed with filtered back projection and commercial iterative reconstruction algorithm (level 3 and 5). Two re

Radiology, Nuclear Medicine and ImagingMedicine
5
Article|127 citations·2020
Preoperative CT-based Deep Learning Model for Predicting Disease-Free Survival in Patients with Lung Adenocarcinomas
Hyungjin Kim, Jin Mo Goo, Kyung Hee Lee, Young Tae Kim, Chang Min Park
SJR Q1Radiology

Background Deep learning models have the potential for lung cancer prognostication, but model output as an independent prognostic factor must be validated with clinical risk factors. Purpose To develop and validate a preoperative CT-based deep learning model for predicting disease-free survival in patients with lung adenocarcinoma. Materials and Methods In this retrospective study, a deep learning model was trained to extract prognostic information from preoperative CT examinations. Data set 1 f

Radiology, Nuclear Medicine and ImagingMedicine
6
Article|67 citations·2013
Pure and Part-Solid Pulmonary Ground-Glass Nodules: Measurement Variability of Volume and Mass in Nodules with a Solid Portion Less than or Equal to 5 mm
Hyungjin Kim, Chang Min Park, Sungmin Woo, Sang Min Lee, Hyun-Ju Lee, Chul‐Gyu Yoo, Jin Mo Goo
SJR Q1Radiology

Mass measurement of GGNs showed measurement variability from -17.7% to 18.6% and may be a useful method in the follow-up of GGNs with solid portions less than or equal to 5 mm.

Pulmonary and Respiratory MedicineMedicine
7
Review|66 citations·2013
Pulmonary subsolid nodules: what radiologists need to know about the imaging features and management strategy
Hyungjin Kim, Chang Min Park, Jae Moon Koh, Sang Min Lee, Jin Mo Goo
SJR Q2Diagnostic and Interventional RadiologyOA

Pulmonary subsolid nodules (SSNs) refer to pulmonary nodules with pure ground-glass nodules and part-solid ground-glass nodules. SSNs are frequently encountered in the clinical setting, such as screening chest computed tomography (CT). The main concern regarding pulmonary SSNs, particularly when they are persistent, has been lung adenocarcinoma and its precursors. The CT manifestations of SSNs help radiologists and clinicians manage these lesions. However, the management plan for SSNs has not pr

Pulmonary and Respiratory MedicineMedicine
8
Article|64 citations·2020
CT-based deep learning model to differentiate invasive pulmonary adenocarcinomas appearing as subsolid nodules among surgical candidates: comparison of the diagnostic performance with a size-based logistic model and radiologists
Hyungjin Kim, Dongheon Lee, Woo Sang Cho, Jung Chan Lee, Jin Mo Goo, Hee Chan Kim, Chang Min Park, Hee Chan Kim, Chang Min Park
SJR Q1European Radiology
Pulmonary and Respiratory MedicineMedicine
9
Article|57 citations·2015
Reduced Field-of-View Diffusion-Weighted Magnetic Resonance Imaging of the Pancreas: Comparison with Conventional Single-Shot Echo-Planar Imaging
Hyungjin Kim, Jeong Min Lee, Jeong Hee Yoon, Jin‐Young Jang, Sun‐Whe Kim, Ji Kon Ryu, Stephan Kannengießer, Joon Koo Han, Byung Ihn Choi
SJR Q1Korean Journal of RadiologyOA

Reduced FOV DWI of the pancreas provides better overall IQ including better anatomic detail, lesion conspicuity and subjective clinical utility.

Radiology, Nuclear Medicine and ImagingMedicine
10
Article|52 citations·2019
CT-defined Visceral Pleural Invasion in T1 Lung Adenocarcinoma: Lack of Relationship to Disease-Free Survival
Hyungjin Kim, Jin Mo Goo, Young Tae Kim, Chang Min Park
SJR Q1Radiology

BackgroundPathologic visceral pleural invasion (pVPI) leads to upstaging from T1 to T2. However, it is unclear whether the CT features for pVPI can be reliably used as a clinical T2 descriptor for preoperative staging.PurposeTo validate the diagnostic accuracy and analyze the prognostic value of CT findings for the prediction of pVPI in patients with resected node-negative lung adenocarcinoma.Materials and MethodsThis retrospective cohort study included clinical T1N0M0 adenocarcinomas resected b

Pulmonary and Respiratory MedicineMedicine
11
Article|50 citations·2014
Influence of radiation dose and iterative reconstruction algorithms for measurement accuracy and reproducibility of pulmonary nodule volumetry: A phantom study
Hyungjin Kim, Chang Min Park, Yong Song, Sang Min Lee, Jin Mo Goo
SJR Q1European Journal of Radiology
Radiology, Nuclear Medicine and ImagingMedicine
12
Article|50 citations·2020
Lung Cancer CT Screening and Lung-RADS in a Tuberculosis-endemic Country: The Korean Lung Cancer Screening Project (K-LUCAS)
Hyungjin Kim, Hyae Young Kim, Jin Mo Goo, Yeol Kim
SJR Q1Radiology

Background Low-dose CT screening for lung cancer in a tuberculosis-endemic country may be less effective because of false-positive results caused by tuberculosis sequelae. Purpose To evaluate the impact of tuberculosis sequelae at CT screening according to the American College of Radiology Lung CT Screening Reporting and Data System (Lung-RADS) using data from the Korean Lung Cancer Screening Project (K-LUCAS). Materials and Methods This is a secondary analysis of K-LUCAS (ClinicalTrials.gov ide

Pulmonary and Respiratory MedicineMedicine
13
Article|48 citations·2020
Prediction of visceral pleural invasion in lung cancer on CT: deep learning model achieves a radiologist-level performance with adaptive sensitivity and specificity to clinical needs
Hyewon Choi, Hyungjin Kim, Wonju Hong, Jongsoo Park, Eui Jin Hwang, Chang Min Park, Young Tae Kim, Jin Mo Goo
SJR Q1European Radiology
Pulmonary and Respiratory MedicineMedicine
14
Review|47 citations·2015
Quantitative Computed Tomography Imaging Biomarkers in the Diagnosis and Management of Lung Cancer
Hyungjin Kim, Chang Min Park, Jin Mo Goo, Joachim E. Wildberger, Hans‐Ulrich Kauczor
SJR Q1Investigative Radiology

Tumor diameter has traditionally been used as a standard metric in terms of diagnosis and prognosis prediction of lung cancer. However, recent advances in imaging techniques and data analyses have enabled novel quantitative imaging biomarkers that can characterize disease status more comprehensively and/or predict tumor behavior more precisely. The most widely used imaging modality for lung tumor assessment is computed tomography. Therefore, we focused on computed tomography imaging biomarkers s

Pulmonary and Respiratory MedicineMedicine
15
Article|45 citations·2013
Gliomas: Application of Cumulative Histogram Analysis of Normalized Cerebral Blood Volume on 3 T MRI to Tumor Grading
Hyungjin Kim, Seung Hong Choi, Ji‐hoon Kim, Inseon Ryoo, Soo Chin Kim, Jeong A Yeom, Hwaseon Shin, Seung Chai Jung, A. Leum Lee, Tae Jin Yun, Chul‐Kee Park, Chul‐Ho Sohn
SJR Q1PLoS ONEOA

Cumulative histogram analysis of nCBV using 3 T MRI can be a useful method for preoperative glioma grading. The nCBV C99 value is helpful in distinguishing high- from low-grade gliomas and grade IV from III gliomas.

GeneticsMedicine

Research Areas

Pulmonary and Respiratory MedicineRadiology, Nuclear Medicine and ImagingInfectious DiseasesRheumatologyEpidemiologyCardiology and Cardiovascular Medicine

Hyoung Jin Kim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。