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We present a technique for automatic brain tumor segmentation in magnetic resonance images, combining a modified version of a Genetic Algorithm Clustering method with an AdaBoost Classifier. In a group of 42 FLAIR images, segmentations produced by the algorithm were compared to the ground truth information produced by radiologists. The mean Dice similarity coefficient reached by the algorithm was 70.3%. In most cases, the AdaBoost classifier increased the quality of the segmentation, improving,doi:10.5220/0006534900770082 dblp:conf/biostec/OliveiraVC18 fatcat:wow36ugl7bgbrf3fxuakl6bxwy