Prostate cancer characterization on MR images using fractal features

Abstract

Classification using the authors' model combining fractal and multifractal features was more accurate than classification using classical texture features (such as Haralick, wavelet, and Gabor filters). Moreover, the method was more robust against signal intensity variations. Although the method was only applied to T2 images, it could be extended to multispectral MR.