NORHA is a novel index for quantifying hippocampal asymmetries in neurodegenerative conditions. It shows promise as a biomarker for detecting unilateral abnormalities, such as hippocampal sclerosis, and correlates positively with the functional cognitive test CDR-SB, indicating its potential in dementia diagnosis.
We develop a deep neural network that automatically extracts contextual features from patches in sketches, trained with 3D models rendered with non-photorealistic techniques. Our method is able to find dense correspondences between real world sketches!
We introduced a fully automated approach to segment the photorceptor layer, evaluate its thickness and track potential disruptions using an ensemble of deep neural networks.