A Machine Learning Approach to Brain Tumors Segmentation Using Adaptive Random Forest Algorithm

In this paper a brain tumor segmentation method is proposed which is based on the Random Forest algorithm. The proposed technique is applied to the brain magnetic resonance images and the performance indices including Dice Similarity Coefficient (DSC) as well as algorithm accuracy (ACC) are calculated that are 98.38% and 97.65%, respectively. The obtained results show that the proposed model can have a good performance when compared with the other segmentation methods. Besides, in this paper the mathematical modeling of the Random Forest algorithm is provided.

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