Image enhancement and noise filtering of ischemic stroke in CT and MRI brain / Mutiara Malek …[et al.]

Ischemic stroke is a condition of dysfunction of certain area in brain due to the decreasing blood supply. The stage of the ischemic stroke can be diagnose by having the CT or MRI of brain. However, the provided information in images from both modalities may contaminated by noise and poor contrast. Noise will degrade the image formation by appeared as irregular granular pattern in the images. Radiographic contrast can be defined as the differences of the degree of density between two adjacent areas. It plays an important role for the observer to distinguish features of interest, for example, defects from the surrounding area. Hence, image enhancement and noise filtering must be applied to improve the image quality and eliminate the distribution of the extreme noise. From the result of study, both adaptive filtering and wiener filtering can be used in removing the noise in order to enhance visualization of the location of infarction or embolism occurs from the ischemic stroke. Another filter method used is averaging filtering which also have the same purpose to eliminate the noise. Then, the image must undergo sharpened process by using unsharp masking to improve the blurring effect. This method can also demonstrate early stroke changes by enhances the detail and resolution of the cortical sulci. Besides, to enhance the image, contrast-limited adaptive histogram equalisation is used to produce the clearer details and brighter of the output images. It enhanced the right lateral horn of the frontal lobe which narrowed that indicate the present of hemorrhage which are one of the factors of ischemic stroke. In addition, the image enhancement by the negative transformation highlight the transformation of original image.