Changes in Brain White Matter Assessed Via Textural Features Using a Neural Network

Data Gathering

DTMR images obtained at the center of corpus collasum from 60 volunteers of age group between 55 and 80) are segmented for white matter using automated segmenting procedure and analysed for age-related changes in brain fiber tracts. The procedure is as follows:

• •

  Obtaining the DTMR images from the volunteers

• •

  Segmenting the image for white matter

• •

  Finding co-occurrence matrix of the quantised white matter image

• •

  Finding the appropriate statistical features from GLCM

• •

  Finding the most suitable features for classification

• •

  Using back propagation neural network, the image is classified against the age.

Image Acquisition

MRI acquisition was performed on a GE 3 Tesla Signa HDX system equipped with an 8-channel brain array coil using a Diffusion Tensor Imaging with Fourier transform. Protocol: Field-of-view (FOV) 240 × 240mm; matrix 256 × 256; TR=7400; Number of diffusion direction = 25; b value = 1000; voxel size 0.9375 × 0.9375 × 5 mm; slice thickness = 5mm; scanning time = 8 min. Scanning done in axial plane parallel to the long axis of the body of corpus callosum. Ten images under each age group, totaling 60 images (on subjects with mean age = 64.4483, SD = 8.7841) from both male and female (with no neurological problem) are considered for the purpose. Image analysis methods are implemented in MATLAB^TM (Version 7.6).