Perceptual model based data embedding in medical images

Abstract

In this work, we propose a perceptual model based technique for embedding patient information in a medical image. The distortions in the diagnostic information-content, which will arise due to data embedding, can be controlled using a Perceptual Quality Measure (PQM). A Perceptual Quality Distortion Measure (PQDM) has been defined to measure the visible distortions between the original image and the processed image. The PQDM increases with the increase in the quantity of data embedded into the image. However it has been shown that the PQDM has different values when the same quantity of data is embedded into different regions inside the image, whereas the peak signal to noise ratio (PSNR) is only dependent on the quantity of embedded-data and does not show any change when the same quantity of data is embedded at different regions in the image. Quantification of correlation between PQDM and the loss in diagnostic information in medical images could play the key role for further work in this research area.