Taejoon Eo
Overview
Explore the profile of Taejoon Eo including associated specialties, affiliations and a list of published articles.
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Articles
11
Citations
137
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0
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Recent Articles
1.
Shin Y, Son G, Hwang D, Eo T
Med Image Anal
. 2025 Feb;
101:103477.
PMID: 39913965
Magnetic resonance imaging (MRI) is an important imaging modality in medical diagnosis, providing comprehensive anatomical information with detailed tissue structures. However, the long scan time required to acquire high-quality MR...
2.
Won H, Lee H, Youn D, Park D, Eo T, Kim W, et al.
Diagnostics (Basel)
. 2024 Sep;
14(17).
PMID: 39272685
Knee effusion, a common and important indicator of joint diseases such as osteoarthritis, is typically more discernible on magnetic resonance imaging (MRI) scans compared to radiographs. However, the use of...
3.
Choi E, Park D, Son G, Bak S, Eo T, Youn D, et al.
Eur Radiol
. 2023 Nov;
34(6):3750-3760.
PMID: 37973631
Objective: This study aims to develop a weakly supervised deep learning (DL) model for vertebral-level vertebral compression fracture (VCF) classification using image-level labelled data. Methods: The training set included 815...
4.
Shin H, Park J, Jun Y, Eo T, Lee J, Kim J, et al.
Eur Radiol
. 2023 May;
33(8):5859-5870.
PMID: 37150781
Objectives: An appropriate and fast clinical referral suggestion is important for intra-axial mass-like lesions (IMLLs) in the emergency setting. We aimed to apply an interpretable deep learning (DL) system to...
5.
Shin H, Lee J, Eo T, Jun Y, Kim S, Hwang D
Taehan Yongsang Uihakhoe Chi
. 2022 Oct;
81(6):1305-1333.
PMID: 36237722
Deep learning has recently achieved remarkable results in the field of medical imaging. However, as a deep learning network becomes deeper to improve its performance, it becomes more difficult to...
6.
Son G, Eo T, An J, Oh D, Shin Y, Rha H, et al.
Diagnostics (Basel)
. 2022 Aug;
12(8).
PMID: 36010210
By automatically classifying the stomach, small bowel, and colon, the reading time of the wireless capsule endoscopy (WCE) can be reduced. In addition, it is an essential first preprocessing step...
7.
Jun Y, Shin H, Eo T, Kim T, Hwang D
Med Image Anal
. 2021 Mar;
70:102017.
PMID: 33721693
Quantitative tissue characteristics, which provide valuable diagnostic information, can be represented by magnetic resonance (MR) parameter maps using magnetic resonance imaging (MRI); however, a long scan time is necessary to...
8.
Eo T, Shin H, Jun Y, Kim T, Hwang D
Med Image Anal
. 2020 Apr;
63:101689.
PMID: 32299061
This study developed a domain-transform framework comprising domain-transform manifold learning with an initial analytic transform to accelerate Cartesian magnetic resonance imaging (DOTA-MRI). The proposed method directly transforms undersampled Cartesian k-space...
9.
Jun Y, Eo T, Shin H, Kim T, Lee H, Hwang D
Magn Reson Med
. 2019 Jan;
81(6):3840-3853.
PMID: 30666723
Purpose: To develop and evaluate a method of parallel imaging time-of-flight (TOF) MRA using deep multistream convolutional neural networks (CNNs). Methods: A deep parallel imaging network ("DPI-net") was developed to...
10.
Jun Y, Eo T, Kim T, Shin H, Hwang D, Bae S, et al.
Sci Rep
. 2018 Jun;
8(1):9450.
PMID: 29930257
Black-blood (BB) imaging is used to complement contrast-enhanced 3D gradient-echo (CE 3D-GRE) imaging for detecting brain metastases, requiring additional scan time. In this study, we proposed deep-learned 3D BB imaging...