Directional weighted spatial fuzzy C-means for segmentation of brain MRI images.

Directional weighted spatial fuzzy C-means for segmentation of brain MRI images. J Xray Sci Technol. 2019 Sep 21;: Authors: Khan SU, Ahmed I, Khan IU, Ullah N, Khan MWJ Abstract Brain and its structure are extremely complex with deep levels of details. Applying image processing methods of brain images is quite useful in many practical application domains. Currently, magnetic resonance imaging (MRI) is a widely used imaging technique and has unique advantage by possessing the capability of providing highly detailed images of soft tissues in brain than other imaging techniques. Many researchers in medical imaging field have been working to develop image processing tools to perform precise segmentation of regions of interest from brain MRI, which can overcome the effects of noise and other imaging artifacts like intensity inhomogeneity introduced in medical images during image acquisition process. In this research work, we proposed and tested a directional weighted optimized Fuzzy C-Means (dwsFCM) method to segment brain MR images. This method works by incorporating the spatial information of the pixels of the images and assigning the directional weights to the neighborhood. In order to validate the proposed segmentation framework, a comprehensive set of experiments have been performed using the standard simulation method and publicly available image datasets. The experimental results showed 95% of accuracy, which indicates that the proposed segmentation fra...
Source: Journal of X-Ray Science and Technology - Category: Radiology Tags: J Xray Sci Technol Source Type: research

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