4 papers
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…
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…