Alzheimer disease diagnosis using the K-means, GLCM and K-NN

المؤلف

Ulaywi, Wid Kazim

المصدر

Journal of Babylon University : Journal of Applied and Pure Sciences

العدد

المجلد 26، العدد 2 (28 فبراير/شباط 2018)، ص ص. 57-65، 9ص.

الناشر

جامعة بابل

تاريخ النشر

2018-02-28

دولة النشر

العراق

عدد الصفحات

9

التخصصات الرئيسية

الرياضيات

الملخص 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.

نمط استشهاد جمعية علماء النفس الأمريكية (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

نمط استشهاد الجمعية الأمريكية للغات الحديثة (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

نمط استشهاد الجمعية الطبية الأمريكية (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

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references : p. 64-65

رقم السجل

BIM-1094077