INTRACRANIAL HEMORRHAGE SEGMENTATION USING NEURAL NETWORK AND RIESZ FRACTIONAL ORDER DERIVATIVE-BASED TEXTURE ENHANCEMENT
This paper explores the application of the U-Net architecture for intracranial hemorrhage segmentation, with a focus on enhancing segmentation accuracy through the incorporation of texture enhancement techniques based on the Riesz fractional order derivatives. The study begins by conducting a review of related works in the field of computed tomography (CT) scan segmentation. At this stage also a suitable dataset is selected.