Recent Advances in Medical Image Processing.

Journal: Acta cytologica
Published Date:

Abstract

BACKGROUND: Application and development of the artificial intelligence technology have generated a profound impact in the field of medical imaging. It helps medical personnel to make an early and more accurate diagnosis. Recently, the deep convolution neural network is emerging as a principal machine learning method in computer vision and has received significant attention in medical imaging. Key Message: In this paper, we will review recent advances in artificial intelligence, machine learning, and deep convolution neural network, focusing on their applications in medical image processing. To illustrate with a concrete example, we discuss in detail the architecture of a convolution neural network through visualization to help understand its internal working mechanism.

Authors

  • Zhen Huang
    Division of Medical Technology Development, Hangzhou Zhiwei Information & Technology Ltd., Hangzhou, Hangzhou, China.
  • Qiang Li
    Department of Dermatology, Air Force Medical Center, PLA, Beijing, People's Republic of China.
  • Ju Lu
    Division of Medical Technology Development, Hangzhou Zhiwei Information & Technology Ltd., Hangzhou, China.
  • Junlin Feng
    Hangzhou Zhiwei Information and Technology Inc., Hangzhou, China.
  • Jiajia Hu
    Hangzhou Zhiwei Information and Technology Inc., Hangzhou, China.
  • Ping Chen
    Department of Infectious Diseases, Renmin Hospital of Wuhan University, Wuhan 430060, China.