Brain Tumor Classification Based on Singular Value Decomposition

Abstract: Every day over 100 adults will be diagnosed with a primary brain tumor and many more will be diagnosed with a cancer. Diagnosing a specific type of brain tumor can be a complicated affair, making confirmation of its diagnosis essential. In this paper we suggested new method for detection of brain tumor based on singular value decomposition (SVD). The algorithm first trained/learned with normal brain MR images, then in the second step the algorithm become capable to classify the brain MR images into healthy and non-healthy image (that have a tumor). The algorithm is trained with 20 of normal brain MR images and tested with 50 brain MR images. The accuracy of this method was up to 97%.

Keywords: MRI, brain tumor, classification, image processing, SVD.