Recent Advances in Medical Image Processing

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.

Automated summary

This paper reviews the recent advances in artificial intelligence, machine learning, and deep convolution neural networks in medical image processing. It also discusses open questions, current trends, and critical challenges faced by medical image processing and artificial intelligence technology. The architecture of a convolution neural network is detailed through visualization to aid in understanding its internal working mechanism.