Recent Advances in Medical Image Processing
Zhen Huang, Qiang Li, Lu Ju, Junlin Feng, Jiajia Hu, Ping Chen
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. SUMMARY: This review discusses several open questions, current trends, and critical challenges faced by medical image processing and artificial intelligence technology.