Enhancing glioma grading in MRI using deep learning approach

Abstract

Cancer remains the second leading cause of mortality globally, and brain tumors newlinecontribute significantly to this statistic, especially as metastatic cancers frequently lead newlineto secondary brain tumors. Gliomas are the most common type of primary brain tumor newlinethat arise from glial cells and show different levels of aggressiveness. Nearly 80% of newlineprimary malignant brain tumors are gliomas, highlighting how important glial cell ab- newlinenormalities are to brain health. They are categorized into low-grade gliomas (LGG), newlinewhich are slow-growing and less aggressive, and high-grade gliomas (HGG), which are newlinerapidly proliferating, highly invasive, and associated with poorer prognoses. The rapid newlineand uncontrolled growth of glial cells in gliomas affects normal brain function, creat- newlineing pressure on nearby tissues and leading to serious neurological problems. Proper newlineclassification and grading of gliomas are crucial for planning treatment and predicting newlineoutcomes effectively newline