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Low grade glioma segmentation using an automatic computational technique in magnetic resonance imaging
(Sociedad Venezolana de Farmacología Clínica y Terapéutica, 2018)
Through this work we propose a computational technique for the segmentation of a brain tumor, identified as low grade glioma (LGG), specifically grade II astrocytoma, which is present in magnetic resonance images (MRI). This technique consists of 3 stages developed in the three-dimensional domain. They are: pre-processing, segmentation and postprocessing. The percent relative error (PrE) is considered to compare the segmentations of the LGG, generated by a neuro- oncologist manually, with the dilated segmentations of the LGG, obtained ...