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Journal of Medical Systems
Published in: Journal of Medical Systems 11/2018

01-11-2018 | Image & Signal Processing

Medical Image Analysis using Convolutional Neural Networks: A Review

Authors: Syed Muhammad Anwar, Muhammad Majid, Adnan Qayyum, Muhammad Awais, Majdi Alnowami, Muhammad Khurram Khan

Published in: Journal of Medical Systems | Issue 11/2018

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Abstract

The science of solving clinical problems by analyzing images generated in clinical practice is known as medical image analysis. The aim is to extract information in an affective and efficient manner for improved clinical diagnosis. The recent advances in the field of biomedical engineering have made medical image analysis one of the top research and development area. One of the reasons for this advancement is the application of machine learning techniques for the analysis of medical images. Deep learning is successfully used as a tool for machine learning, where a neural network is capable of automatically learning features. This is in contrast to those methods where traditionally hand crafted features are used. The selection and calculation of these features is a challenging task. Among deep learning techniques, deep convolutional networks are actively used for the purpose of medical image analysis. This includes application areas such as segmentation, abnormality detection, disease classification, computer aided diagnosis and retrieval. In this study, a comprehensive review of the current state-of-the-art in medical image analysis using deep convolutional networks is presented. The challenges and potential of these techniques are also highlighted.
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Metadata
Title
Medical Image Analysis using Convolutional Neural Networks: A Review
Authors
Syed Muhammad Anwar
Muhammad Majid
Adnan Qayyum
Muhammad Awais
Majdi Alnowami
Muhammad Khurram Khan
Publication date
01-11-2018
Publisher
Springer US
Published in
Journal of Medical Systems / Issue 11/2018
Print ISSN: 0148-5598
Electronic ISSN: 1573-689X
DOI
https://doi.org/10.1007/s10916-018-1088-1

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