Multimodal brain tumor segmentation using ensemble of forest method

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Conference Article

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)


In this paper, we have proposed a cascaded ensemble method based on Random Forest, named as Ensemble-of-Forest, (EoF). Instead of classifying huge amount of data with a single forest, we proposed two stage ensemble method for Multimodal Brain Tumor Segmentation problem. Identification of Tumor region and its sub-regions poses challenge in terms of variations in intensity, location etc. from patient to patient. We identify the initial region of interest (ROI) by linear combination of FLAIR and T2 modality. For each training scan/ROI, we define a Random Forest as first stage of ensemble method. For a test ROI, collect a set of similarly seen ROI and hence forest based on mutual information criteria and collect majority voting to classify voxels in it. We have reported results on BRATS 2017 dataset in this paper.

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