The motivation was to develop an assessment method to measure (in)visible differences between the original and the processed images in MR brain angiography as a method of evaluation of the status of the vessel segments (i.e. the existence of the occlusion or intracerebral vessels damaged as aneurysms). Generally, the image quality is limited, so we improve the performance of the evaluation through digital image processing. The goal is to determine the best processing method that allows an accurate assessment of patients with cerebrovascular diseases. A total of 10 MR brain angiography images were processed by the following techniques: histogram equalization, Wiener filter, linear contrast adjustment, contrastlimited adaptive histogram equalization, bias correction and Marr- Hildreth filter. Each original image and their processed images were analyzed into the stacking procedure so that the same vessel and its corresponding diameter have been measured. Original and processed images were evaluated by measuring the vessel diameter (in pixels) on an established direction and for the precise anatomic location. The vessel diameter is calculated using the plugin ImageJ. Mean diameter measurements differ significantly across the same segment and for different processing techniques. The best results are provided by the Wiener filter and linear contrast adjustment methods and the worst by Marr-Hildreth filter. [ABSTRACT FROM AUTHOR]
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