Abstract:
Primary brain tumors can be malignant (cancerous) or benign (non-cancerous). Out of primary brain tumors,
gliomas are the most common and, high grade gliomas carry a poor prognosis. In our paper, we present a technique to
segment the glioma cells in Magnetic Resonance Imaging (MRI) using faster Region based Convolutional Neural
Network (R-CNN) and edge detection techniques in image processing algorithms. This study identifies the region of
interest that is glioma cells, with higher confidence level and localize the tumor on the MRI with the tumor mask.
Further, analysis shows that with the proposed technique it is possible to achieve an average detection accuracy,
sensitivity, Dice score and confidence level of 99.81%, 87.72%, 91.14% and 93.6% respectively
