activity
20182023
most citedPose-Aware Instance Segmentation Framework from Cone Beam CT Images for Tooth Segmentation

99 citations · 297 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CV2023★ 10 cited

3DTeethSeg'22: 3D Teeth Scan Segmentation and Labeling Challenge

Achraf Ben-Hamadou, Oussama Smaoui, Ahmed Rekik +29

Teeth localization, segmentation, and labeling from intra-oral 3D scans are essential tasks in modern dentistry to enhance dental diagnostics, treatment planning, and population-ba…

cs.CV2022

Accurate Ground-Truth Depth Image Generation via Overfit Training of Point Cloud Registration using Local Frame Sets

Jiwan Kim, Minchang Kim, Yeong-Gil Shin +1

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 sing…

cs.CV2022

Voxel-wise Adversarial Semi-supervised Learning for Medical Image Segmentation

Chae Eun Lee, Hyelim Park, Yeong-Gil Shin +1

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 anno…

eess.IV2021★ 19 cited

Cardiac Segmentation on CT Images through Shape-Aware Contour Attentions

Sanguk Park, Minyoung Chung

Cardiac segmentation of atriums, ventricles, and myocardium in computed tomography (CT) images is an important first-line task for presymptomatic cardiovascular disease diagnosis.…

cs.CV2021

Voxel-level Siamese Representation Learning for Abdominal Multi-Organ Segmentation

Chae Eun Lee, Minyoung Chung, Yeong-Gil Shin

Recent works in medical image segmentation have actively explored various deep learning architectures or objective functions to encode high-level features from volumetric data owin…

cs.CV2021

Tooth Instance Segmentation from Cone-Beam CT Images through Point-based Detection and Gaussian Disentanglement

Jusang Lee, Minyoung Chung, Minkyung Lee +1

Individual tooth segmentation and identification from cone-beam computed tomography images are preoperative prerequisites for orthodontic treatments. Instance segmentation methods…

cs.CV2020

Robust Kernel-based Feature Representation for 3D Point Cloud Analysis via Circular Convolutional Network

Seunghwan Jung, Yeong-Gil Shin, Minyoung Chung

Feature descriptors of point clouds are used in several applications, such as registration and part segmentation of 3D point clouds. Learning discriminative representations of loca…

cs.CV2020★ 55 cited

Individual Tooth Detection and Identification from Dental Panoramic X-Ray Images via Point-wise Localization and Distance Regularization

Minyoung Chung, Jusang Lee, Sanguk Park +4

Dental panoramic X-ray imaging is a popular diagnostic method owing to its very small dose of radiation. For an automated computer-aided diagnosis system in dental clinics, automat…

cs.CV2020★ 31 cited

Liver Segmentation in Abdominal CT Images via Auto-Context Neural Network and Self-Supervised Contour Attention

Minyoung Chung, Jingyu Lee, Jeongjin Lee +1

Accurate image segmentation of the liver is a challenging problem owing to its large shape variability and unclear boundaries. Although the applications of fully convolutional neur…

cs.CV2020★ 99 cited

Pose-Aware Instance Segmentation Framework from Cone Beam CT Images for Tooth Segmentation

Minyoung Chung, Minkyung Lee, Jioh Hong +5

Individual tooth segmentation from cone beam computed tomography (CBCT) images is an essential prerequisite for an anatomical understanding of orthodontic structures in several app…

cs.CV2019★ 50 cited

Automatic Registration between Cone-Beam CT and Scanned Surface via Deep-Pose Regression Neural Networks and Clustered Similarities

Minyoung Chung, Jingyu Lee, Wisoo Song +4

Computerized registration between maxillofacial cone-beam computed tomography (CT) images and a scanned dental model is an essential prerequisite in surgical planning for dental im…

cs.CV2018★ 33 cited

Deeply Self-Supervised Contour Embedded Neural Network Applied to Liver Segmentation

Minyoung Chung, Jingyu Lee, Minkyung Lee +2

Objective: Herein, a neural network-based liver segmentation algorithm is proposed, and its performance was evaluated using abdominal computed tomography (CT) images. Methods: A fu…