Continual medical image denoising based on triplet neural networks collaboration.

Journal: Computers in biology and medicine
Published Date:

Abstract

BACKGROUND: When multiple tasks are learned consecutively, the old model parameters may be overwritten by the new data, resulting in the phenomenon that the new task is learned and the old task is forgotten, which leads to catastrophic forgetting. Moreover, continual learning has no mature solution for image denoising tasks.

Authors

  • Xianhua Zeng
    Chongqing Key Laboratory of Image Cognition, College of Computer Science and Technology, Chongqing University of Posts and Telecommunication, Chongqing 400065, China. Electronic address: zengxh@cqupt.edu.cn.
  • Yongli Guo
    School of Computer Science and Technology/School of Artificial Intelligence, Chongqing University of Posts and Telecommunications, Chongqing 400065, China. Electronic address: 15351286281@163.com.
  • Laquan Li
  • Yuhang Liu
    School of Computer Science and Technology, North University of China, Taiyuan, China.