Search Results - "Eo, Taejoon"

KIKI‐net: cross‐domain convolutional neural networks for reconstructing undersampled magnetic resonance images by Eo, Taejoon, Jun, Yohan, Kim, Taeseong, Jang, Jinseong, Lee, Ho‐Joon, Hwang, Dosik

“…Purpose To demonstrate accurate MR image reconstruction from undersampled k‐space data using cross‐domain convolutional neural networks (CNNs) Methods…”
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Deep Learning-Based Joint Effusion Classification in Adult Knee Radiographs: A Multi-Center Prospective Study by Won, Hyeyeon, Lee, Hye Sang, Youn, Daemyung, Park, Doohyun, Eo, Taejoon, Kim, Wooju, Hwang, Dosik

“…Knee effusion, a common and important indicator of joint diseases such as osteoarthritis, is typically more discernible on magnetic resonance imaging (MRI)…”
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Small Bowel Detection for Wireless Capsule Endoscopy Using Convolutional Neural Networks with Temporal Filtering by Son, Geonhui, Eo, Taejoon, An, Jiwoong, Oh, Dong Jun, Shin, Yejee, Rha, Hyenogseop, Kim, You Jin, Lim, Yun Jeong, Hwang, Dosik

“…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…”
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No-reference Automatic Quality Assessment for Colorfulness-Adjusted, Contrast-Adjusted, and Sharpness-Adjusted Images Using High-Dynamic-Range-Derived Features by Jang, Jinseong, Jang, Hanbyol, Eo, Taejoon, Bang, Kihun, Hwang, Dosik

“…Image adjustment methods are one of the most widely used post-processing techniques for enhancing image quality and improving the visual preference of the…”
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The Latest Trends in Attention Mechanisms and Their Application in Medical Imaging by Shin, Hyungseob, Lee, Jeongryong, Eo, Taejoon, Jun, Yohan, Kim, Sewon, Hwang, Dosik

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Deep model-based magnetic resonance parameter mapping network (DOPAMINE) for fast T1 mapping using variable flip angle method by Jun, Yohan, Shin, Hyungseob, Eo, Taejoon, Kim, Taeseong, Hwang, Dosik

“…•Deep model-based magnetic resonance (MR) parameter mapping network (DOPAMINE).•Mapping network estimates initial parameter maps from undersampled k-space…”
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Accelerating Cartesian MRI by domain-transform manifold learning in phase-encoding direction by Eo, Taejoon, Shin, Hyungseob, Jun, Yohan, Kim, Taeseong, Hwang, Dosik

“…•Domain-transform manifold learning algorithm to accelerate Cartesian MRI reconstruction.•Applying 1D inverse Fourier transform along the data-acquisition…”
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Weakly supervised deep learning for diagnosis of multiple vertebral compression fractures in CT by Choi, Euijoon, Park, Doohyun, Son, Geonhui, Bak, Seongwon, Eo, Taejoon, Youn, Daemyung, Hwang, Dosik

“…Objective This study aims to develop a weakly supervised deep learning (DL) model for vertebral-level vertebral compression fracture (VCF) classification using…”
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Joint Deep Model-based MR Image and Coil Sensitivity Reconstruction Network (Joint-ICNet) for Fast MRI by Jun, Yohan, Shin, Hyungseob, Eo, Taejoon, Hwang, Dosik

“…Magnetic resonance imaging (MRI) can provide diagnostic information with high-resolution and high-contrast images. However, MRI requires a relatively long scan…”
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Relevance-CAM: Your Model Already Knows Where to Look by Lee, Jeong Ryong, Kim, Sewon, Park, Inyong, Eo, Taejoon, Hwang, Dosik

“…With increasing fields of application for neural networks and the development of neural networks, the ability to explain deep learning models is also becoming…”
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Parallel imaging in time‐of‐flight magnetic resonance angiography using deep multistream convolutional neural networks by Jun, Yohan, Eo, Taejoon, Shin, Hyungseob, Kim, Taeseong, Lee, Ho‐Joon, Hwang, Dosik

“…Purpose To develop and evaluate a method of parallel imaging time‐of‐flight (TOF) MRA using deep multistream convolutional neural networks (CNNs). Methods A…”
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Deep learning referral suggestion and tumour discrimination using explainable artificial intelligence applied to multiparametric MRI by Shin, Hyungseob, Park, Ji Eun, Jun, Yohan, Eo, Taejoon, Lee, Jeongryong, Kim, Ji Eun, Lee, Da Hyun, Moon, Hye Hyeon, Park, Sang Ik, Kim, Seonok, Hwang, Dosik, Kim, Ho Sung

“…Objectives An appropriate and fast clinical referral suggestion is important for intra-axial mass-like lesions (IMLLs) in the emergency setting. We aimed to…”
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SDC-UDA: Volumetric Unsupervised Domain Adaptation Framework for Slice-Direction Continuous Cross-Modality Medical Image Segmentation by Shin, Hyungseob, Kim, Hyeongyu, Kim, Sewon, Jun, Yohan, Eo, Taejoon, Hwang, Dosik

“…Recent advances in deep learning-based medical image segmentation studies achieve nearly human-level performance in fully supervised manner. However, acquiring…”
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Deep-learned 3D black-blood imaging using automatic labelling technique and 3D convolutional neural networks for detecting metastatic brain tumors by Jun, Yohan, Eo, Taejoon, Kim, Taeseong, Shin, Hyungseob, Hwang, Dosik, Bae, So Hi, Park, Yae Won, Lee, Ho-Joon, Choi, Byoung Wook, Ahn, Sung Soo

“…Black-blood (BB) imaging is used to complement contrast-enhanced 3D gradient-echo (CE 3D-GRE) imaging for detecting brain metastases, requiring additional scan…”
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Comparision study of stereoscopy in computed tomography : Projection versus MIP by Younguk Kim, Jinseong Jang, Taejoon Eo, Dosik Hwang

“…This paper introduces a stereoscopy in Computed Tomography (CT), and two projection methods to create a stereoscopy. One is summing projection and the other is…”
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High-SNR multiple T 2 ()-contrast magnetic resonance imaging using a robust denoising method based on tissue characteristics by Eo, Taejoon, Kim, Taeseong, Jun, Yohan, Lee, Hongpyo, Ahn, Sung Soo, Kim, Dong-Hyun, Hwang, Dosik

“…To develop an effective method that can suppress noise in successive multiecho T (*)-weighted magnetic resonance (MR) brain images while preventing filtering…”
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Phase mask enhancement for multi-echo MR images using a novel denoising method based on tissue relaxation properties by Taejoon Eo, Younguk Kim, Jinseong Jang, Dosik Hwang

“…Multiple-echo magnetic resonance images are a series of images acquired at different echo times. Especially, phase images of multiple-echo images are often…”
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High‐SNR multiple T2()‐contrast magnetic resonance imaging using a robust denoising method based on tissue characteristics by Eo, Taejoon, Kim, Taeseong, Jun, Yohan, Lee, Hongpyo, Ahn, Sung Soo, Kim, Dong‐Hyun, Hwang, Dosik

“…Purpose To develop an effective method that can suppress noise in successive multiecho T2(*)‐weighted magnetic resonance (MR) brain images while preventing…”
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The Latest Trends in Attention Mechanisms and Their Application in Medical Imaging by Hyungseob Shin, Jeongryong Lee, Taejoon Eo, Yohan Jun, Sewon Kim, Dosik Hwang

“…Deep learning has recently achieved remarkable results in the field of medical imaging. However, as a deep learning network becomes deeper to improve its…”
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SDC-UDA: Volumetric Unsupervised Domain Adaptation Framework for Slice-Direction Continuous Cross-Modality Medical Image Segmentation by Shin, Hyungseob, Kim, Hyeongyu, Kim, Sewon, Jun, Yohan, Eo, Taejoon, Hwang, Dosik

“…Recent advances in deep learning-based medical image segmentation studies achieve nearly human-level performance in fully supervised manner. However, acquiring…”
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