Exploring foci of:
arXiv (Cornell University)
Deeply Self-Supervising Edge-to-Contour Neural Network Applied to Liver Segmentation.
August 2018 • Minyoung Chung, Jingyu Lee, Min-Kyung Lee, Jeongjin Lee, Yeong-Gil Shin
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 volumetric image segmentation problem. To guide a neural network to accurately delineate a target liver object, the network was deeply supervised by applying the adaptive self-supervision scheme to derive the essential contour, which acted as a complement with the global shape. The …
Artificial Intelligence
Segmentation Fault
Computer Science
Convolutional Neural Network
Computer Vision
Image Segmentation
Philosophy