Designing a Digital System for Enhancing, Coloring, Encryption and Decryption of X-ray Medical Image

The most often requested test in every radiology department, chest X-rays are crucial for the diagnosis of several chest conditions. Despite the numerous technological advancements in radiology, interpreting a chest X-ray remains a challenging task because of the images' propensity for noise, low contrast, and blurriness. Additionally, extraneous information obstructs the analysis of actual issues with human chest structures, making it challenging to analyze X-ray images effectively. In this study, we used a novel algorithm to improve digital chest radiographs and, consequently, improve the diagnosis of specific diseases. We achieved this by applying a number of procedures, such as enhancing the fundamental features of the images and refining the colors by using an experimental equation and varying the values of the equation’s primary parameter. The ribs, sternum, and clavicle, as well as the soft tissues, were all clearly visible in the final images that we examined, which is a positive sign that the suggested algorithm improved the diagnosis. Because there are many hacking operations and instances of personal and medical information being stolen, these medical pictures in the modern world of telemedicine need to be safeguarded from users who are not permitted to see the information contained in them. Given that the figure illustrates the connections between the pixels, the chaotic logistic encryption algorithm-based picture encryption technique has been used. contiguous to confirm this encryption algorithm’s encryption effectiveness. Use MATLAB to show the encryption in order to illustrate how the method affects the encrypted picture data. picture analysis naturally discovers that the chaotic logistic encryption method performs better at encrypting picture data. Additionally, the statistical data successfully obscures the original image’s features, making it resistant to statistical assaults based on image pixel values. This technique was used on encrypted medical images, and a value of 4 falls within the encryption range.