A Survey of Deep Learning Based Methods in Medical Image Processing

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

Journal Name: Current Signal Transduction Therapy

Volume 16 , Issue 2 , 2021


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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.

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

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Article Details

VOLUME: 16
ISSUE: 2
Year: 2021
Published on: 13 December, 2019
Page: [101 - 114]
Pages: 14
DOI: 10.2174/1574362415666191213145321

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