Abstract
Automatic CAD system able to detect correctly the unhealthy brain in magnetic resonance imaging (MRI) scanning is represented in this paper. The new system exploited Discrete Wavelet Transform (DWT) and Bag-of-Words (BoW) to extract image features. Support vector machine (SVM) was used in classification step. We employed 256×256 images from three datasets (DS-66, DS-160, DS-255) provided by Harvard Medical School, to evaluate our method. 10∗k-fold stratified Cross Validation (CV) technique was applied to validate the system performance. The Accuracy reached respectively 100%, 100%, and 99.61% for DS-66, DS-160, and DS-255 datasets. The overall computation time is about 0.027 s for each MR image. A comparative study with several works showed efficiency and robustness of our scheme.