Automatic-segmentation-of-glioma-based-on-MRI-K-space-data

In contemporary medical practice, Magnetic Resonance Imaging (MRI) is indispensable for the diagnosis, analysis, and surgical planning of gliomas. However, the precision of MRI-based segmentation is significantly contingent upon image quality. To address this limitation, we present an innovative method that enables segmentation directly from K-space data. Our findings illustrate the viability of this novel segmentation approach, demonstrating its potential utility in enhancing the accuracy of glioma diagnostics.