Iridology based diagnosis of kidney abnormalities due to diabetes mellitus

N. Padmasini; J. Aarthi; U. Deepika; R. Deepshikhaa

Authors

N. Padmasini Department of Biomedical Engineering, Rajalakshmi Engineering College, Chennai, India 602 105
J. Aarthi Department of Biomedical Engineering, Rajalakshmi Engineering College, Chennai, India 602 105
U. Deepika Department of Biomedical Engineering, Rajalakshmi Engineering College, Chennai, India 602 105
R. Deepshikhaa Department of Biomedical Engineering, Rajalakshmi Engineering College, Chennai, India 602 105

Keywords:

GLCM, histogram, iridology, iriscope, iris chart, kidney, Random Forest Classification.

Abstract

Iridology is a very useful technique to diagnose the abnormalities in various parts of our human body. The human iris is connected to all parts of the body through nerve strands. Iridologists see the eyes as windows into the body's state of health through iris images. Iridologists claim they can use the iridology charts to distinguish between healthy organs and those that are overactive, inflamed, or distressed through the change in pigmentation or due to lacunae formation in the various iris regions. As the diabetic population is increasing day by day, it is crucial to detect early changes in the kidneys due to Type 1 or Type 2 diabetes, in order to avoid kidney failure. This work aims to diagnose the presence of any abnormality in the kidney due to diabetes mellitus using iris images as well as iridology charts and hence, automatically categorizing normal and abnormal cases using the Random Forest Classification algorithm. Through this algorithm 83.33 percent accuracy is achieved. As a pilot study twenty four normal and abnormal images were taken and analyzed. However, more images are to be analysed to claim iridology as a tool for diagnosing kidney ailments.

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