Medical Image Analysis using Deep Learning: A Review
- Resource Type
- Conference
- Authors
- Nisa, Syed Qamrun; Ismail, Amelia Ritahani; Ali, M. A. B. MD; Khan, Mohammad Shadab
- Source
- 2020 IEEE 7th International Conference on Engineering Technologies and Applied Sciences (ICETAS) Engineering Technologies and Applied Sciences (ICETAS) 2020 IEEE 7th International Conference on. :1-3 Dec, 2020
- Subject
- Bioengineering
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Deep learning
Image segmentation
Recurrent neural networks
Conferences
Object detection
Convolutional neural networks
Biomedical imaging
medical image
medical image analysis
- Language
Over the recent past, deep learning is one of the core research directions which has gained a great deal of attention due to its outstanding performance in the area of medical image analysis. This paper aims to present a review of deep learning concepts related to medical imaging. We examine the use of deep learning for medical image analysis including segmentation, object detection and classification. Deep learning techniques including convolutional neural networks (CNNs), recurrent neural network (RNNs) and auto- encoder (AE) are also discussed in this paper.