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- Publisher
- Karger
- Copyright
- © 2020 S. Karger AG, Basel
- ISSN
- 0001-5547
- eISSN
- 1938-2650
- DOI
- 10.1159/000510992
- Publisher site
- See Article on Publisher Site
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.
Journal
Acta Cytologica – Karger
Published: Aug 1, 2021
Keywords: Medical imaging; Convolution neural network; Deep learning; Artificial intelligence