VBM-fuzzy computing of MR brain volume for proper intensity diagnosis of Alzheimer's

At its simplest, volume calculation of MR Image segmented & further soft computed to estimate the affected intensity of Alzheimer's disease is dealt with this paper. It is concerned with Voxel Based Morphometry to render the first part segmentation. The result gives an active region which further needs an estimation to justify the diagnosis. As in this case the image is in form of voxels. When properly processed, classified images can represent foundations for diagnostic purposes. A VBM - fuzzy approach was used to take advantage of Voxel Based Morphometry's ability to fine segmentation based on voxel comparisons of GM, WM & CSF and membership degrees and functions of fuzzy logic, respectively. The method of VBM is done with SPM. The method is based on the spatial properties of the MR Brain image features and makes use of SPM multi-scaled representations of the image. A fuzzy classifier is created on basis of the previous segmented data. The classes were represented as fuzzy sets with degrees of memberships. Each voxel was assigned certain degrees of membership for each of the fuzzy subset created according to voxel intensities. Classified voxels were finally shown as separate images each representing a set. The method showed high quality classification for images of complex components in determining the intensity of Alzheimer's. This approach would be highly useful in the biomedical field ,as it goes in hand with the medical practitioner's to help the human mankind.