A Survey of Deep Learning Based Methods in Medical Image Processing

Title:A Survey of Deep Learning Based Methods in Medical Image Processing

Volume: 16 Issue: 2

Author(s): Yinglei Song*, Mohammad N.A. Rana, Junfeng Qu and Chunmei Liu

Affiliation:

• School of Electronics and Information Science, Jiangsu University of Science and Technology, Zhenjiang, 212003,China

Keywords: Medical image processing, deep learning models, review, convolutional neural networks, recurrent neural networks, fitting lines.

Abstract:

Introduction: Recently, deep learning based methods have become an important approach to the accurate analysis of medical images.

Materials and Methods: This paper provides a comprehensive survey of the most important deep learning based methods that have been developed for medical image processing. A number of important contributions made in the last five years are summarized and surveyed.

Results: Specifically, deep learning-based algorithms developed for image segmentation, image classification, registration, object detection and other important problems are reviewed.

Conclusion: In addition, an overview of challenges that currently exist in the field and potential directions for future research is provided at the end of the survey.

Cite this article as:

Song Yinglei *, Rana N.A. Mohammad , Qu Junfeng and Liu Chunmei , A Survey of Deep Learning Based Methods in Medical Image Processing, Current Signal Transduction Therapy 2021; 16 (2) . https://dx.doi.org/10.2174/1574362415666191213145321