The accurate automatic segmentation of gliomas and its intra-tumoral structures is important not only for treatment planning but also for follow-up evaluations. Several methods based on 2D and 3D Deep Neural Networks (DNN) have been developed to segment brain tumors and to classify different categories of tumors from different MRI modalities. However, these networks are […]

Spiking Neural Networks (SNNs) have shown favorable performance recently. Nonetheless, the time-consuming computation on neuron level and complex optimization limit their real-time application. Curiosity has shown great performance in brain learning, which helps biological brains grasp new knowledge efficiently and actively. Inspired by this leaning mechanism, we propose a curiosity-based SNN (CBSNN) model, which contains […]

With a lipid-rich environment and elevated oxygen consumption, the central nervous system (CNS) is subject to intricate regulation by lipid-derived electrophiles (LDEs). Investigations into oxidative damage and chronic LDE generation in neural disorders have spurred the development of tools that can detect and catalog the gamut of LDE-adducted proteins. Despite these advances, deconstructing the precise […]