Analysis of MRI and OCT Images for the Early Diagnosis of Alzheimer's Disease Using Wavelet Networks
Alzheimer disease (AD) a progressive neurodegenerative disorder, is the most common cause of dementia in the old age population. Previous clinical and histological studies suggest that the neurodegenerative process, which affects the brain, may also affect the retina of AD patients. Any disease modifying treatments which are developed are most possibly to be achieving success if initiated early in the process, and this needs that we tend to develop reliable, validated and economical ways to diagnose Alzheimer's kind brain disease. However, despite comprehensive searches, no single test has shown adequate sensitivity and specificity, and it is likely that a combination will be needed. Profiling of human body parameter using computers can be utilized for the early diagnosis of Alzheimer's disease. In this paper we have focused on Magnetic Resonance Imaging (MRI) and Optical Coherence Tomography (OCT) imaging techniques for the early diagnosis of AD. For this purpose we have developed a method based on Wavelet Networks (WN) known as Fixed Grid Wavelet Networks (FGWN) for the analysis of OCT and MRI images. This method provides reliable and validated results for both OCT and MRI images.