Yeong-Gil Shin
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View article: GA-VAE: Enhancing Local Feature Representation in VQ-VAE Through Genetic Algorithm-Based Token Optimization
GA-VAE: Enhancing Local Feature Representation in VQ-VAE Through Genetic Algorithm-Based Token Optimization Open
This paper introduces GA-VAE, a fine-tuning framework that enhances local feature representation in pre-trained Vector Quantized-VAE (VQ-VAE) models through genetic algorithm-based optimization. While VQ-VAE models have shown promise in le…
View article: Hybrid model-based and deep learning-based metal artifact reduction method in dental cone-beam computed tomography
Hybrid model-based and deep learning-based metal artifact reduction method in dental cone-beam computed tomography Open
Objective: To present a hybrid approach that incorporates a constrained beam-hardening estimator (CBHE) and deep learning (DL)-based post-refinement for metal artifact reduction in dental cone-beam computed tomography (CBCT). \n\nMethods: …
View article: 3DTeethSeg'22: 3D Teeth Scan Segmentation and Labeling Challenge
3DTeethSeg'22: 3D Teeth Scan Segmentation and Labeling Challenge Open
Teeth localization, segmentation, and labeling from intra-oral 3D scans are essential tasks in modern dentistry to enhance dental diagnostics, treatment planning, and population-based studies on oral health. However, developing automated a…
View article: DEHA-Net: A Dual-Encoder-Based Hard Attention Network with an Adaptive ROI Mechanism for Lung Nodule Segmentation
DEHA-Net: A Dual-Encoder-Based Hard Attention Network with an Adaptive ROI Mechanism for Lung Nodule Segmentation Open
Measuring pulmonary nodules accurately can help the early diagnosis of lung cancer, which can increase the survival rate among patients. Numerous techniques for lung nodule segmentation have been developed; however, most of them either rel…
View article: Dual-Stage Deeply Supervised Attention-Based Convolutional Neural Networks for Mandibular Canal Segmentation in CBCT Scans
Dual-Stage Deeply Supervised Attention-Based Convolutional Neural Networks for Mandibular Canal Segmentation in CBCT Scans Open
Accurate segmentation of mandibular canals in lower jaws is important in dental implantology. Medical experts manually determine the implant position and dimensions from 3D CT images to avoid damaging the mandibular nerve inside the canal.…
View article: Accurate Ground-Truth Depth Image Generation via Overfit Training of Point Cloud Registration using Local Frame Sets
Accurate Ground-Truth Depth Image Generation via Overfit Training of Point Cloud Registration using Local Frame Sets Open
Accurate three-dimensional perception is a fundamental task in several computer vision applications. Recently, commercial RGB-depth (RGB-D) cameras have been widely adopted as single-view depth-sensing devices owing to their efficient dept…
View article: Voxel-wise Adversarial Semi-supervised Learning for Medical Image Segmentation
Voxel-wise Adversarial Semi-supervised Learning for Medical Image Segmentation Open
Semi-supervised learning for medical image segmentation is an important area of research for alleviating the huge cost associated with the construction of reliable large-scale annotations in the medical domain. Recent semi-supervised appro…
View article: Monocular Depth Estimation of Indoor Environments Using Enhanced Rgb-D Dataset
Monocular Depth Estimation of Indoor Environments Using Enhanced Rgb-D Dataset Open
View article: Robust Kernel-Based Feature Representation for 3d Point Cloud Analysis Via Circular Convolutional Network
Robust Kernel-Based Feature Representation for 3d Point Cloud Analysis Via Circular Convolutional Network Open
View article: Accurate Ground-Truth Depth Image Generation Via Overfit Training of Point Cloud Registration Using Local Frame Sets
Accurate Ground-Truth Depth Image Generation Via Overfit Training of Point Cloud Registration Using Local Frame Sets Open
View article: Voxel-level Siamese Representation Learning for Abdominal Multi-Organ Segmentation
Voxel-level Siamese Representation Learning for Abdominal Multi-Organ Segmentation Open
Recent works in medical image segmentation have actively explored various deep learning architectures or objective functions to encode high-level features from volumetric data owing to limited image annotations. However, most existing appr…
View article: Tooth Instance Segmentation from Cone-Beam CT Images through Point-based Detection and Gaussian Disentanglement
Tooth Instance Segmentation from Cone-Beam CT Images through Point-based Detection and Gaussian Disentanglement Open
Individual tooth segmentation and identification from cone-beam computed tomography images are preoperative prerequisites for orthodontic treatments. Instance segmentation methods using convolutional neural networks have demonstrated groun…
View article: Metal artifact reduction method based on a constrained beam-hardening estimator for polychromatic x-ray CT
Metal artifact reduction method based on a constrained beam-hardening estimator for polychromatic x-ray CT Open
Beam hardening in x-ray computed tomography (CT) is inevitable because of the polychromatic x-ray spectrum and energy-dependent attenuation coefficients of materials, leading to the underestimation of artifacts arising from projection data…
View article: Robust Kernel-based Feature Representation for 3D Point Cloud Analysis via Circular Convolutional Network
Robust Kernel-based Feature Representation for 3D Point Cloud Analysis via Circular Convolutional Network Open
Feature descriptors of point clouds are used in several applications, such as registration and part segmentation of 3D point clouds. Learning discriminative representations of local geometric features is unquestionably the most important t…
View article: Robust Kernel-based Feature Representation for 3D Point Cloud Analysis via Circular Graph Convolutional Network
Robust Kernel-based Feature Representation for 3D Point Cloud Analysis via Circular Graph Convolutional Network Open
Feature descriptors of point clouds are used in several applications, such as registration and part segmentation of 3D point clouds. Learning discriminative representations of local geometric features is unquestionably the most important t…
View article: Geometric robust descriptor for 3D point cloud.
Geometric robust descriptor for 3D point cloud. Open
We propose rotation robust and density robust local geometric descriptor. Local geometric feature of point cloud is used in many applications, for example, to find correspondences in 3D registration and to segment local regions. Usually, a…
View article: Volumetric lung nodule segmentation using adaptive ROI with multi-view residual learning
Volumetric lung nodule segmentation using adaptive ROI with multi-view residual learning Open
Accurate quantification of pulmonary nodules can greatly assist the early diagnosis of lung cancer, enhancing patient survival possibilities. A number of nodule segmentation techniques, which either rely on a radiologist-provided 3-D volum…
View article: 치아 신경관 식별을위한 자동 시상면 검출법
치아 신경관 식별을위한 자동 시상면 검출법 Open
Identification of the mandibular canal path in Computed Tomography (CT) scans is important in dental implantology. Typically, prior to the implant planning, dentists find a sagittal plane where the mandibular canal path is maximally observ…
View article: Ghosted Illustration Rendering using Depth-based Blending Techniques
Ghosted Illustration Rendering using Depth-based Blending Techniques Open
Ghosted illustration is an effective tool to simultaneously visualize interior and exterior structures while preserving clear shape cues. We propose a novel framework that combines 3D blending technique, which uses depth information of the…
View article: Pose-aware instance segmentation framework from cone beam CT images for tooth segmentation
Pose-aware instance segmentation framework from cone beam CT images for tooth segmentation Open
View article: Deeply self-supervised contour embedded neural network applied to liver segmentation
Deeply self-supervised contour embedded neural network applied to liver segmentation Open
View article: Depth-of-Field Rendering Using Progressive Lens Sampling in Direct Volume Rendering
Depth-of-Field Rendering Using Progressive Lens Sampling in Direct Volume Rendering Open
Direct volume rendering is a widely used technique for extracting information from three-dimensional scalar fields acquired by measurement or numerical simulation. However, the translucency of direct volume rendering to express the interna…
View article: Deeply Self-Supervising Edge-to-Contour Neural Network Applied to Liver Segmentation.
Deeply Self-Supervising Edge-to-Contour Neural Network Applied to Liver Segmentation. Open
Objective: Herein, a neural network-based liver segmentation algorithm is proposed, and its performance was evaluated using abdominal computed tomography (CT) images. Methods: A fully convolutional network was developed to overcome the vol…
View article: Effects Of Process Parameters On Cu Powder Synthesis Yield And Particle Size In A Wet-Chemical Process
Effects Of Process Parameters On Cu Powder Synthesis Yield And Particle Size In A Wet-Chemical Process Open
This study presents a simple wet-chemical process to prepare several micron-size Cu powders. Moreover, changes in powder synthesis yield and particle size are examined with different solvents, synthesis temperatures, and amounts of reducin…
View article: Fast and Accurate Semiautomatic Segmentation of Individual Teeth from Dental CT Images
Fast and Accurate Semiautomatic Segmentation of Individual Teeth from Dental CT Images Open
DIn this paper, we propose a fast and accurate semiautomatic method to effectively distinguish individual teeth from the sockets of teeth in dental CT images. Parameter values of thresholding and shapes of the teeth are propagated to the n…