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- Title
Medical Image Analysis using Convolutional Neural Networks: A Review.
- Authors
Anwar, Syed Muhammad; Majid, Muhammad; Qayyum, Adnan; Awais, Muhammad; Alnowami, Majdi; Khan, Muhammad Khurram
- 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.
- Subjects
EVALUATION of diagnostic imaging; ARTIFICIAL intelligence; BIOMEDICAL engineering; DIAGNOSTIC imaging; DIGITAL image processing; MACHINE learning; COMPUTERS in medicine; ARTIFICIAL neural networks; THREE-dimensional imaging; IMAGE retrieval; IMAGE storage &; retrieval systems; COMPUTER-aided diagnosis
- Publication
Journal of Medical Systems, 2018, Vol 42, Issue 11, p1
- ISSN
0148-5598
- Publication type
Article
- DOI
10.1007/s10916-018-1088-1