Interactive e diagnosis steganography techniques for securing patient information embedded in medical images

Abstract

Volumes of medical images are rapidly generated and have shown newlinea tremendous change in the medical field and to manage them effectively has newlinebecome a great challenge This thesis studies about the embedding techniques newlineand the development of innovative medical image retrieval based on texture newlinefeatures and accuracy The data hiding is wholly based on histogram shifting newlinebased wavelet transforms and CBIR model The objective of the proposed newlineresearch work is to embed the patient information s in a medical image with newlinerespect to the region of interest and thereby to construct the accurate values of capacity PSNR based on the image retrieval of healthcare management newlinesystems The first algorithm with a lifting scheme is used to hide the data of newlinethe patient history in the medical image and to recover the information newlinewithout any distortion and loss has been extracted successfully While newlineembedding the IWT coefficient is utilized and decomposed image newlinewatermarks are embedded with corresponding resolutions However the newlineimage quality does not degrade from watermarked image In the preferred newlineregion of interest the retrieval of the image gives high PSNR Peak Signal to newlineNoise Ratio and Mean Square error MSE newline newline