Secure magnetic resonance image transmission and tumor detection techniques

The transmission of important medical diagnostic, MRI (Magnetic Resonance Imaging) images are vulnerable to third party hackers who does spoofing and they are able to introduce faulty and noisy data that damage the transmission data, which hinders the proper medical diagnostics, research and credibility of labs and doctors, there is a clear lack of awareness and lack of proper security measures taken in transmission of MRI images in the present labs, hospitals and research centers. This project is helpful to reduce the problem of secure transmission of medical images. There are many algorithms which can be applied to these medical images. This project is helpful to provide good security to medical images during transmission. Tumor detection or prediction in medical science is a very complex and expensive job, which is not yet been addressed properly and no proper graphical user interface exists in an open source environment. This project is dedicated to analyze the best tumor detection from an MRI brain image after several segmentation methods such as K-means Clustering and Watershed segmentation. Security is realized considering various techniques for encryption and decryption of the image. The encryption technique finally selected after the survey was based on Rivest, Shamir & Adleman [RSA] algorithm.