Hackjoon Shim
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View article: Image quality and radiation dose of reduced-dose abdominopelvic computed tomography (CT) with silver filter and deep learning reconstruction
Image quality and radiation dose of reduced-dose abdominopelvic computed tomography (CT) with silver filter and deep learning reconstruction Open
View article: Preoperative Rotator Cuff Tear Prediction from Shoulder Radiographs using a Convolutional Block Attention Module-Integrated Neural Network
Preoperative Rotator Cuff Tear Prediction from Shoulder Radiographs using a Convolutional Block Attention Module-Integrated Neural Network Open
Research question: We test whether a plane shoulder radiograph can be used together with deep learning methods to identify patients with rotator cuff tears as opposed to using an MRI in standard of care. Findings: By integrating convolutio…
View article: Injection rate, scanning position, and values of parameters on pulmonary computed tomography perfusion in normal Beagles
Injection rate, scanning position, and values of parameters on pulmonary computed tomography perfusion in normal Beagles Open
OBJECTIVE This study evaluated the effects of scanning position and contrast medium injection rate on pulmonary CT perfusion (CTP) images in healthy dogs. ANIMALS 7 healthy Beagles. METHODS Experiments involved 4 conditions: dorsal and ste…
View article: Improving the Reproducibility of Computed Tomography Radiomic Features Using an Enhanced Hierarchical Feature Synthesis Network
Improving the Reproducibility of Computed Tomography Radiomic Features Using an Enhanced Hierarchical Feature Synthesis Network Open
Radiomics has gained popularity as a quantitative analysis method for medical images. However, computed tomography (CT) scans are performed using various parameters, such as X-ray dose and reconstruction kernels, which is a fundamental rea…
View article: Assessment of Image Quality of Coronary CT Angiography Using Deep Learning-Based CT Reconstruction: Phantom and Patient Studies
Assessment of Image Quality of Coronary CT Angiography Using Deep Learning-Based CT Reconstruction: Phantom and Patient Studies Open
Background: In coronary computed tomography angiography (CCTA), the main issue of image quality is noise in obese patients, blooming artifacts due to calcium and stents, high-risk coronary plaques, and radiation exposure to patients. Objec…
View article: Generative adversarial network with radiomic feature reproducibility analysis for computed tomography denoising
Generative adversarial network with radiomic feature reproducibility analysis for computed tomography denoising Open
We demonstrated that the well-tuned GAN architecture outperforms the well-known CT denoising methods. Our study is the first to introduce radiomics reproducibility analysis as an evaluation metric for CT denoising. We look forward that the…
View article: The effectiveness of post-processing head and neck CT angiography using contrast enhancement boost technique
The effectiveness of post-processing head and neck CT angiography using contrast enhancement boost technique Open
Background and purpose This study aimed to investigate the potential of contrast enhancement (CE)-boost technique in the head and neck computed tomography (CT) angiography in terms of the objective and subjective image quality. Materials a…
View article: Reconstruction of Partially Broken Vascular Structures in X-Ray Images via Vesselness-Loss-Based Multi-Scale Generative Adversarial Networks
Reconstruction of Partially Broken Vascular Structures in X-Ray Images via Vesselness-Loss-Based Multi-Scale Generative Adversarial Networks Open
Coronary artery procedures are primarily performed based on X-ray angiography images. However, coronary arteries in X-ray images are often partially broken, complicating diagnoses and procedures owing to lack of visibility. In this paper, …
View article: A Novel Computed Tomography Image Reconstruction for Improving Visualization of Pulmonary Vasculature: Comparison Between Preprocessing and Postprocessing Images Using a Contrast Enhancement Boost Technique
A Novel Computed Tomography Image Reconstruction for Improving Visualization of Pulmonary Vasculature: Comparison Between Preprocessing and Postprocessing Images Using a Contrast Enhancement Boost Technique Open
Objective This study aimed to evaluate chest computed tomography (CT) angiography image quality using the contrast enhancement (CE)–boost technique compared with conventional images. Methods Forty patients who underwent contrast-enhanced c…
View article: Bayesian approaches for Quantifying Clinicians' Variability in Medical Image Quantification
Bayesian approaches for Quantifying Clinicians' Variability in Medical Image Quantification Open
Medical imaging, including MRI, CT, and Ultrasound, plays a vital role in clinical decisions. Accurate segmentation is essential to measure the structure of interest from the image. However, manual segmentation is highly operator-dependent…
View article: Improvement in Image Quality and Visibility of Coronary Arteries, Stents, and Valve Structures on CT Angiography by Deep Learning Reconstruction
Improvement in Image Quality and Visibility of Coronary Arteries, Stents, and Valve Structures on CT Angiography by Deep Learning Reconstruction Open
DLR reconstruction provided better images than FBP and hybrid IR reconstruction.
View article: Improvement of depiction of the intracranial arteries on brain CT angiography using deep learning reconstruction
Improvement of depiction of the intracranial arteries on brain CT angiography using deep learning reconstruction Open
To evaluate the ability of a commercialized deep learning reconstruction technique to depict intracranial vessels on the brain computed tomography angiography and compare the image quality with filtered-back-projection and hybrid iterative…
View article: Reconnection of fragmented parts of coronary arteries using local geometric features in X-ray angiography images
Reconnection of fragmented parts of coronary arteries using local geometric features in X-ray angiography images Open
View article: Bayesian Estimation of Geometric Morphometric Landmarks for Simultaneous Localization of Multiple Anatomies in Cardiac CT Images
Bayesian Estimation of Geometric Morphometric Landmarks for Simultaneous Localization of Multiple Anatomies in Cardiac CT Images Open
We propose a robust method to simultaneously localize multiple objects in cardiac computed tomography angiography (CTA) images. The relative prior distributions of the multiple objects in the three-dimensional (3D) space can be obtained th…
View article: Multi-Scale Conditional Generative Adversarial Network for Small-Sized Lung Nodules Using Class Activation Region Influence Maximization
Multi-Scale Conditional Generative Adversarial Network for Small-Sized Lung Nodules Using Class Activation Region Influence Maximization Open
Automatic detection and classification of thoracic diseases using deep learning algorithms have many applications supporting radiologists’ diagnosis and prognosis. However, in the medical field, the class-imbalanced problem is extremely co…
View article: Generation of High-Resolution Chest X-rays using Multi-scale Conditional Generative Adversarial Network with Attention
Generation of High-Resolution Chest X-rays using Multi-scale Conditional Generative Adversarial Network with Attention Open
View article: Identification of coronary arteries in CT images by Bayesian analysis of geometric relations among anatomical landmarks
Identification of coronary arteries in CT images by Bayesian analysis of geometric relations among anatomical landmarks Open
View article: Robust Coronary Artery Segmentation in 2D X-ray Images using Local Patch-based Re-connection Methods
Robust Coronary Artery Segmentation in 2D X-ray Images using Local Patch-based Re-connection Methods Open
View article: Maximum a posteriori estimation method for aorta localization and coronary seed identification
Maximum a posteriori estimation method for aorta localization and coronary seed identification Open
View article: Geodesic Distance Algorithm for Extracting the Ascending Aorta from 3D CT Images
Geodesic Distance Algorithm for Extracting the Ascending Aorta from 3D CT Images Open
This paper presents a method for the automatic 3D segmentation of the ascending aorta from coronary computed tomography angiography (CCTA). The segmentation is performed in three steps. First, the initial seed points are selected by minimi…
View article: Intensity-vesselness Gaussian mixture model (IVGMM) for 2D + t segmentation of coronary arteries for X-ray angiography image sequences
Intensity-vesselness Gaussian mixture model (IVGMM) for 2D + t segmentation of coronary arteries for X-ray angiography image sequences Open
It is concluded that the IVGMM tracking could obtain reasonable segmentation accuracy outperforming conventional vessel enhancement methods and object tracking methods.
View article: An Automatic Algorithm for Vessel Segmentation in X-Ray Angiogram using Random Forest
An Automatic Algorithm for Vessel Segmentation in X-Ray Angiogram using Random Forest Open
The purpose of this study is to develop an automatic algorithm for vessel segmentation in X-Ray angiogram using Random Forest (RF). The proposed algorithm is composed of the following steps: First, the multiscale hessian-based filtering is…
View article: Effects of Iterative Reconstruction Algorithm, Automatic Exposure Control on Image Quality, and Radiation Dose: Phantom Experiments with Coronary CT Angiography Protocols
Effects of Iterative Reconstruction Algorithm, Automatic Exposure Control on Image Quality, and Radiation Dose: Phantom Experiments with Coronary CT Angiography Protocols Open
In this study, we investigated the effects of an iterative reconstruction algorithm and an automatic exposure control (AEC) technique on image quality and radiation dose through phantom experiments with coronary computed tomography (CT) an…
View article: Predicting Peri-Device Leakage of Left Atrial Appendage Device Closure Using Novel Three-Dimensional Geometric CT Analysis
Predicting Peri-Device Leakage of Left Atrial Appendage Device Closure Using Novel Three-Dimensional Geometric CT Analysis Open
Angles between the IAS and LAA orifice might be a novel anatomical parameter for predicting peri-device leakage after LAA device closure. In addition, 3D CT analysis of the LA and LAA orifice could be used to identify clinically favorable …