Skip Navigation
Skip to contents
Filter

ARTICLE TYPE

more+
SELECT FILTER
 
Close

PUBLICATION DATE

9 results
Display

Radiologists’ Solutions for COVID-19 in Korea

Jung JI

No abstract available.
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Radiomics and Deep Learning from Research to Clinical Workflow: Neuro-Oncologic Imaging

Park JE, Kickingereder P, Kim HS

Imaging plays a key role in the management of brain tumors, including the diagnosis, prognosis, and treatment response assessment. Radiomics and deep learning approaches, along with various advanced physiologic imaging...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Halo, Reversed Halo, or Both? Atypical Computed Tomography Manifestations of Coronavirus Disease (COVID-19) Pneumonia: The “Double Halo Sign”

Poerio A, Sartoni M, Lazzari G, Valli M, Morsiani M, Zompatori M

The epidemic of 2019 novel coronavirus, later named as coronavirus disease (COVID-19), began in Wuhan, China in December 2019 and has spread rapidly worldwide. Early diagnosis is crucial for the...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Current Status of Etiology, Epidemiology, Clinical Manifestations and Imagings for COVID-19

Jiang MD, Zu ZY, Schoepf UJ, Savage RH, Zhang XL, Lu GM, Zhang LJ

Coronavirus disease 2019 (COVID-19) is a transmissible respiratory disease that was initially reported in Wuhan, China in December 2019. With the alarming levels of COVID-19 spread worldwide, the World Health...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Combined Hepatocellular-Cholangiocarcinoma: Changes in the 2019 World Health Organization Histological Classification System and Potential Impact on Imaging-Based Diagnosis

Kim TH, Kim H, Joo I, Lee JM

Combined hepatocellular-cholangiocarcinoma (cHCC-CCA) is a primary liver cancer (PLC) with both hepatocytic and cholangiocytic phenotypes. Recently, the World Health Organization (WHO) updated its histological classification system for cHCC-CCA. Compared to the...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Incremental Image Noise Reduction in Coronary CT Angiography Using a Deep Learning-Based Technique with Iterative Reconstruction

Hong JH, Park EA, Lee W, Ahn C, Kim JH

Objective: To assess the feasibility of applying a deep learning-based denoising technique to coronary CT angiography (CCTA) along with iterative reconstruction for additional noise reduction. Materials and Methods: We retrospectively enrolled...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Incidence and Risk Factors of Nausea and Vomiting after Exposure to Low-Osmolality Iodinated Contrast Media in Children: A Focus on Preparative Fasting

Ha JY, Choi YH, Cho YJ, Lee S, Lee SB, Choi G, Cheon JE, Kim WS

Objective: To evaluate the incidence and risk factors of emetic complications associated with the intravenous administration of low-osmolality iodinated contrast media (ICM) in children undergoing computed tomography (CT). Materials and Methods:...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Implementation of a Deep Learning-Based ComputerAided Detection System for the Interpretation of Chest Radiographs in Patients Suspected for COVID-19

Hwang EJ, Kim H, Yoon SH, Goo JM, Park CM

Objective: To describe the experience of implementing a deep learning-based computer-aided detection (CAD) system for the interpretation of chest X-ray radiographs (CXR) of suspected coronavirus disease (COVID-19) patients and investigate...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close
Sonographic Assessment of the Extent of Extrathyroidal Extension in Thyroid Cancer

Chung SR, Baek JH, Choi YJ, Sung TY, Song DE, Kim TY, Lee JH

Objective: This study aimed to determine the sonographic features suggestive of extrathyroidal extension (ETE) of thyroid cancers. Materials and Methods: We retrospectively reviewed the sonographic images of 1656 consecutive patients who...
CITED
export Copy
Close
SHARE
Twitter Facebook
Close

Go to Top

Copyright © 2024 by Korean Association of Medical Journal Editors. All rights reserved.     E-mail: koreamed@kamje.or.kr