99 citations · 287 across the 14 of their papers we have counts for
14 papers
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…
MESAHA-Net: Multi-Encoders based Self-Adaptive Hard Attention Network with Maximum Intensity Projections for Lung Nodule Segmentation in CT Scan
Muhammad Usman, Azka Rehman, Abd Ur Rehman +5
Accurate lung nodule segmentation is crucial for early-stage lung cancer diagnosis, as it can substantially enhance patient survival rates. Computed tomography (CT) images are wide…
Dual-Stage Deeply Supervised Attention-based Convolutional Neural Networks for Mandibular Canal Segmentation in CBCT Scans
Azka Rehman, Muhammad Usman, Rabeea Jawaid +6
Accurate segmentation of mandibular canals in lower jaws is important in dental implantology. Medical experts determine the implant position and dimensions manually from 3D CT imag…
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…
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…
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…
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…
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…
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…
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…
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…
Volumetric Lung Nodule Segmentation using Adaptive ROI with Multi-View Residual Learning
Muhammad Usman, Byoung-Dai Lee, Shi Sub Byon +2
Accurate quantification of pulmonary nodules can greatly assist the early diagnosis of lung cancer, which can enhance patient survival possibilities. A number of nodule segmentatio…
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…
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…