Brain Tumor Segmentation Based on Random Forest
Journal Title: Memoirs of the Scientific Sections - Year 2016, Vol 0, Issue
Abstract
In this article we present a discriminative model for tumor detection from multimodal MR images. The main part of the model is built around the random forest (RF) classifier. We created an optimization algorithm able to select the important features for reducing the dimensionality of data. This method is also used to find out the training parameters used in the learning phase. The algorithm is based on random feature properties for evaluating the importance of the variable, the evolution of learning errors and the proximities between instances. The detection performances obtained have been compared with the most recent systems, offering similar results.
Authors and Affiliations
László Lefkovits, Szidónia Lefkovits, Mircea-Florin Vaida
Keywords
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