A proposed Alzheimer's disease diagnosing system based on clustering and segmentation techniques

Author

Muhammad, Sarah J.

Source

Engineering and Technology Journal

Issue

Vol. 36, Issue 2B (28 Feb. 2018), pp.160-165, 6 p.

Publisher

University of Technology

Publication Date

2018-02-28

Country of Publication

Iraq

No. of Pages

6

Main Subjects

Information Technology and Computer Science

Abstract EN

Alzheimer's-disease (AD) is one of the prevalent diseases that afflict the elderly.

The medical field defines Alzheimer is the destruction of brain cells so that the person loses knowledge and perception, afflict both sexes and is called dementia.

The medical field often suffers from accurate diagnosis and detection of the disease in the early stages.

This paper presents a diagnostic approach of Alzheimer based on K-mean clustering algorithm with Markov random field segmentation on Magnetic Reasoning Images (MRI) to build software able to help the medical staff identifying and diagnosis the disease.

The experimental result shows that 91% accuracy is achieved, which demonstrate the system's reliability in the medical diagnostic environment

American Psychological Association (APA)

Muhammad, Sarah J.. 2018. A proposed Alzheimer's disease diagnosing system based on clustering and segmentation techniques. Engineering and Technology Journal،Vol. 36, no. 2B, pp.160-165.
https://search.emarefa.net/detail/BIM-899567

Modern Language Association (MLA)

Muhammad, Sarah J.. A proposed Alzheimer's disease diagnosing system based on clustering and segmentation techniques. Engineering and Technology Journal Vol. 36, no. 2B (2018), pp.160-165.
https://search.emarefa.net/detail/BIM-899567

American Medical Association (AMA)

Muhammad, Sarah J.. A proposed Alzheimer's disease diagnosing system based on clustering and segmentation techniques. Engineering and Technology Journal. 2018. Vol. 36, no. 2B, pp.160-165.
https://search.emarefa.net/detail/BIM-899567

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p. 164-165

Record ID

BIM-899567