Detection of Dementia and Classification of its Stage Using Image Processing
Keywords:
Dementia, Stages, MRI, Evaluation parameters, Watershed segmentation, MSERAbstract
Humans are increasingly being diagnosed with dementia, a disease that can seriously impair their quality of life. With the development of cutting-edge medical technology, it is crucial to precisely detect and identify dementia as soon as possible so that necessary action may be performed. The purpose of the manuscript is to present a precise approach for determining dementia and its stage from MRI images. This is accomplished by combining pre- and post-image processing methods with the watershed segmentation and threshold algorithms. The suggested method not only locates the affected region but also improves image quality using noise removal methods. When validated with a variety of evaluation criteria, including as Peak Signal-to-Noise Ratio (PSNR) Structural Similarity Index Measure (SSIM), Entropy Feature Similarity Index Measure (FSIM), Normalize Cross Correlation (NCC), Normalized Absolute Error (NAE) and stand out when compared to other comparable existing algorithms.
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