GUI Based Brain Tumor Identification System by Detecting Infected Region through a Combination of Region Growing, Cryptography, and Digital Watermarking Technique

A new type of brain tumor identification system is proposed and analyzed in this paper by detecting Infected Region using a combination of Region Growing Algorithm, Cryptography and Digital Watermarking. The information related to patients contained in the Electronic Patient Record (EPR), Region of Infection (ROI), doctor's name and diagnosis from symptoms are encrypted and embedded in the tomographic image itself using the proposed methodology - a combination of the Rivest-Shamir-Adelman (RSA) encryption and bit plane slicing watermarking technique. The infected region is identified through region growing and contour detection algorithm which needs to be perfect for accurate ROI identification resulting in a better treatment. The image quality metrics show that the proposed GUI based brain tumor diagnostic system is good enough for successful recovery of all the embedded information and is found to be similar to the embedded information.