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A subfield of computer science that studies algorithms for digital synthesis and manipulate visual information is Computer graphics. Computer graphics include computational techniques to perform visual and geometric content manipulation. It aims on the computational and mathematical foundations of image generation and processing (Draper & Beveridge, 2001, Mora B et al, 2009, & Peternier A et al, 2006). Image processing is a rapidly developing domain of computers. Improvements in digital imaging technology, processors, and mass storage device made the field grow. Digital image processing allows the expansion of image features of interest and mitigates details unrelated to a given application and then extract precious information. Image processing uses computer algorithms on digital images. It allows use of a wide range of algorithms to be applied on input image data, and avoids problems such as interference of noise and signal distortion during processing, (Gonzalez & Woods, 2008, Rodriguez et al., 2008).
CAD broadly refers to “the use of computer algorithms to aid the image interpretation process”. Most CAD systems are about detection, which is why CAD can also stand for computer aided detection. CAD is now widely used as a general term, including computerized extraction of quantitative measurements from medical images. From the point of view of algorithm development this is natural, because detection and quantification use similar underlying techniques, and because they are both parts of the diagnostic process. In this paper a CAD tool for interactive image processing of medical image is proposed. It provides a platform for medical image processing techniques that are more accurate and flexible. MATLAB was used for processing of images using human data in different formats. In addition to this user can use functional tools like determining the value of pixel in the image, obtain histogram, horizontal and vertical profiles of selected lines of the image, color maps of CT window that include CT bone, CT spine, CT mediastinal, auto adjustment of global intensity and selective intensity, image smoothening, manual and auto thresholding. All the mentioned functions are integrated in a Graphical User Interface which is a user friendly image processing technique that could be of clinical use to assist for image analysis and diagnosis purpose.