Automated Meningioma Detection and Segmentation Using Deep Neural Networks

Introduction: Though tumor volume and growth rate assessment are a central part of surgical planning and surveillance in meningioma patients, these can be time consuming and potentially inaccurate task when done using the presently available manual or semiautomatic tumor segmentation methods. Machine learning approaches have the potential to allow for automated meningioma detection and segmentation on magnetic resonance imaging (MRI).