Angiogenesis transforms gliomas from low-to-high-grade. Vasculature-properties are of essential prognostic-value within grade-III and IV glioma as compared to grade-II. High-resolution susceptibility-weighted imaging (SWI) improves the diagnostic accuracy1. Existing Semi-quantitative methods are user-dependent which manually counts intra-tumoral-susceptibility-signal-intensities (ITSS); a combination of haemorrhage and vasculature. Haemorrhage contributes to false ITSS-count and subsequently to misclassification of tumor-grading. We propose a non-invasive segmentation-based-quantitative approach that calculates the R2-Star relaxivity maps of ITSS, automatically removes haemorrhages from ITSS based on high-R2-Star relaxivity of haemorrhage and finally calculate microvasculature volume within glioma. The proposed-method scores over the existing semi-quantitative method in-terms-of ITSS-estimation and grading-accuracy.