A novel texture extraction and classification model with t1 weighted mri for alzheimers disease

Abstract

Among the neurological disorders, Alzheimer s disease is one of the leading cause of fatality in the past decade. In America, there were over 5.7 million people affected by Alzheimer s Disease(AD) and an alarming 200,000 people who were less than 60 years, had got this aging dementia in 2018. The typical indicators of Alzheimer s dementia are disorientation, delusion, confusion, mental decline, difficulty in thinking, and understanding. AD detection at pre-clinical stage is important to enhance the quality of life of the patients. Neuroscientists develop various machine learning techniques to produce tools that can automatically recognize Alzheimer s disease at an early stage. Mathematical transformations like textures, wavelets, curvelets, and shearlets are used effectively in several medical image processing applications like brain tumour classification, human parts labeling, segmentation, and cancer detection. In this research, a 3D brain MRI based new texture extraction method is proposed and analyzed.