Alzheimer disease diagnosis using the K-means, GLCM and K-NN
Author
Source
Journal of Babylon University : Journal of Applied and Pure Sciences
Issue
Vol. 26, Issue 2 (28 Feb. 2018), pp.57-65, 9 p.
Publisher
Publication Date
2018-02-28
Country of Publication
Iraq
No. of Pages
9
Main Subjects
Abstract EN
Investigation of medical images have major consequence in the field of treatment.in this work ,MR images have been used to distinguish the normal brain from brain with Alzheimer disease .Texture is an native property of all surfaces it contains important facts about the structural organization of the surfaces and their connections neighboring area.
In direction to classify texture must be segmented into a number of section that has the similar properties, for this purpose we used k- means algorithm with GLCM for feature extraction ,finally we used k-nearest neighbor algorithm to distinguish between normal and abnormal brain.
American Psychological Association (APA)
Ulaywi, Wid Kazim. 2018. Alzheimer disease diagnosis using the K-means, GLCM and K-NN. Journal of Babylon University : Journal of Applied and Pure Sciences،Vol. 26, no. 2, pp.57-65.
https://search.emarefa.net/detail/BIM-1094077
Modern Language Association (MLA)
Ulaywi, Wid Kazim. Alzheimer disease diagnosis using the K-means, GLCM and K-NN. Journal of Babylon University : Journal of Applied and Pure Sciences Vol. 26, no. 2 (2018), pp.57-65.
https://search.emarefa.net/detail/BIM-1094077
American Medical Association (AMA)
Ulaywi, Wid Kazim. Alzheimer disease diagnosis using the K-means, GLCM and K-NN. Journal of Babylon University : Journal of Applied and Pure Sciences. 2018. Vol. 26, no. 2, pp.57-65.
https://search.emarefa.net/detail/BIM-1094077
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 64-65
Record ID
BIM-1094077