Early detection of Alzheimer's using digital image processing through iridology, an alternative method

Abstract

Over the years, alternative medicine has carried out numerous systematic studies of the eye, proposing as an analytical support to the iridology, which studies the alterations of the iris in correspondence with the organs of the human body. This is why it presents the opportunity to investigate and learn about certain neuronal diseases, specifically Alzheimer's based on digital image processing. For this, the use of mathematical models based on specialized software (Matlab), determines the characteristics of the iris establishing criteria or patterns to determine the existence or not of Alzheimer's. For this we have: i) The Fourier Transform to normalize the image; ii) The Hough Transform to locate circles in an image. In addition some learning methods based on three multi-layer classifiers were used: ZeroR, Naïve Bayes and Multi-layer Perceptron. Finally, to distinguish between the different types of pathologies, several samples must be used and well identified, that is, the data must be consistent and with a good resolution to avoid influencing the results.