Automated brain data segmentation and pattern recognition using ANN .

In this project we implement an artificial neural network (ANN) algorithm to perform the segmentation of brain MRI data. The multispectral characteristics of MR images with different modalities such as T1, T2 and PD are exploited to segment different brain tissues. The ANN algorithm used in this implementation is the Learning Vector Quantization (LVQ) network. The images required for training and test are obtained from a simulated brain database integrated in the McConell Brain Imaging Center (McBIC) of McGill University’s Montreal Neurological Institute. The results of the segmentation algorithms are qualitatively compared to the phantom images to mask each tissue. Our results suggest excellent brain tissue segmentation. We plan to exploit our results in formulating biologically plausible models for automated tumor detection.