8 papers
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…
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…