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Abstract #2190

Automatic Segmentation of Optic Pathway Gliomas Using Multiparametric Mri Methods

Liat Ben Sira1, Lior Weizman2, Leo Joskowicz2, Ronit Precel1, Shlomi Constantini3,4, Dafna Ben Bashat5

1Department of Radiology , Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel; 2School of Eng and Computer Science, The Hebrew Univeristy of Jerusalem, Jerusalem, Israel; 3The Paediatric Neurosurgery Department, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel; 4Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel; 5The Wohl Institute for Advanced Imaging, Brain Imaging Center, Tel Aviv Sourasky Medical Center , Tel-Aviv, Israel

Accurate and consistent volumetric measurements of optic pathway gliomas (OPG), the most common tumor in the brain in patients with Neurofibromatosis, are clinically crucial. In this study we present an automatic method for segmentation of OPGs from multi-spectral MRI datasets. The method effectively incorporates prior location of the OPG, its shape and intensity and accurately identifies the boundaries in a consistent and repeatable manner. The method was tested on 15 data sets, the optimal threshold was derived from a receiver operating characteristic curve, and a significant correlation was obtained between the volume calculated using this method compared to manual measurements.