Deep Learning: Classification and Automated Detection Earlier of Alzheimer's Disease Using Brain MRI Images
- 1. Faculty of Engineering, School of Computing, University Technology of Malaysia, Johar Bahru (Malaysia)
- 2. UTM-IRDA MaGICX, Institute of Human Centered Engineering, Universiti Teknologi Malaysia (Malaysia)
Description
Alzheimer's disease (AD) progression can be avoided by conducting diagnosis beforehand. This diagnosis acquired quick preventive care which could be possibly done by specialists. Fast and accurate evaluation at the earliest and most challenging stage were required to detect in the diagnosis of AD. In this paper, previous studies were reviewed into a better approach that recognizes the presence of disease in sagittal magnetic resonance automatically (MRI) images that are unusually used. The MRI brain images were used to identify and distinguish characteristics using a range of characteristics recognition techniques. The review of research papers on Alzheimer's Disease published in reputable journals from 2017 to 2020 were presented and discussion of various strategies related to the latest tools used in early diagnosis is our main focus in this study, which could enable researchers to understand current algorithms and techniques in this area, and eventually develop new and more effective algorithms. (paper)
Availability note (English)
Available from http://dx.doi.org/10.1088/1742-6596/1892/1/012009Additional details
Identifiers
Publishing Information
- Journal Title
- Journal of Physics. Conference Series (Online)
- Journal Volume
- 1892
- Journal Issue
- 1
- Journal Page Range
- [9 p.]
- ISSN
- 1742-6596
Conference
- Title
- International Laser Technology and Optics Symposium; Photonics Meeting 2020 (ILATOSPM)
- Dates
- 22-23 Oct 2020
- Place
- Johor (Malaysia)
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 53082341
- Subject category
- S62: RADIOLOGY AND NUCLEAR MEDICINE; S97: MATHEMATICAL METHODS AND COMPUTING;
- Resource subtype / Literary indicator
- Conference
- Descriptors DEI
- BRAIN; DETECTION; DISEASES; MACHINE LEARNING; MAGNETIC RESONANCE; NMR IMAGING
- Descriptors DEC
- ALGORITHMS; ARTIFICIAL INTELLIGENCE; BODY; CENTRAL NERVOUS SYSTEM; DIAGNOSTIC TECHNIQUES; LEARNING; MATHEMATICAL LOGIC; NERVOUS SYSTEM; ORGANS; RESONANCE