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Lesion detection using Gabor-based saliency field mapping

In this paper, we present a method that detects lesions in two-dimensional (2D) cross-sectional brain images. By calculating the major and minor axes of the brain, we calculate an estimate of the background, without any a priori information, to use in inverse filtering. Shape saliency computed by a Gabor filter bank is used to further refine the results of the inverse filtering. The proposed algorithm was tested on different images of "The Whole Brain Atlas" database. The experimental results have produced 93% classification accuracy in processing 100 arbitrary images, representing different kinds of brain lesion.