Using morphological transforms to enhance the contrast of medical images

Medical imaging plays an important role in monitoring the patient's health condition and providing an effective treatment. However, the existence of several objects overlapping in an image and the close proximity of adjacent pixels values in medical images make the diagnostic process a difficult task. To cope with such problems, this paper presents a new method based on morphological transforms to enhance the quality of various medical images. In this method, a diskshaped mask whose size fits that of the original input image is chosen for morphological operations. Afterward, the proposed filter from the Top-Hat transforms is applied to the image, using the chosen mask in a multi-step process. At each step, the size of the mask is increased. Consequently, an enhanced image is provided for each mask size. The number of required steps and the final enhanced image are determined based on the Contrast Improvement Ratio (CIR) measure. Indeed, this approach applies an exfoliation process on the images, in which one or several objects in the image are prominently manifested using morphological filter, hence provide an appropriate image for analysis. The results in this research indicate that the proposed approach makes a better contrast and works much better than the other existing methods in improving the quality of medical images. (C) 2015 The Authors. The Egyptian Society of Radiology and Nuclear Medicine. Production and hosting by Elsevier B. V. This is an open access article under the CC BY- NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).