Identifying Lymphoma in Microscopy Images with Classificational Cellular Automata

Abstract

We present the results of a supervised approach for identification of follicular lymphomas in microscopy images. A new feature extraction approach is presented. The proposed discriminative features intend to emphasize the distinction among pixels on follicle contour. Additionally those features are used for supervised learning using classificational cellular automata (CCA) approach with the aim to obtain a general decision support model for classification of follicle contours on the microscopy images