Titlebook: Advances in Visual Computing; 13th International S George Bebis,Richard Boyle,Jonathan Ventura Conference proceedings 2018 Springer Nature

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Automatic Registration of Serial Cerebral Angiography: A Comparative Reviewring treatment effectiveness, recovery, and detection of diseases onset. While medical image registration algorithms have been largely evaluated on MRI and CT, less attention has been given to Digital Subtraction Angiography (DSA). DSA of the brain is the method of choice for the diagnosis of numero

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Skull Stripping Using Confidence Segmentation Convolution Neural Network muscles, greatly hinder the accuracy of further automatic diagnosis. To extract important brain tissue quickly, we developed a model named Confidence Segmentation Convolutional Neural Network (CSCNet). CSCNet takes the form of a Fully Convolutional Network (FCN) that adopts an encoder-decoder archi

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Heart Modeling by Convexity Preserving Segmentation and Convex Shape Decompositionof Left Ventricle (LV) and Right Ventricle (RV) from cardiac magnetic resonance images. The main contributions are two-fold. First, we introduce a convexity preserving mechanism in the level set framework, which is helpful for overcoming the difficulties arised from the overlap between intensities o

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Biomimetic Perception Learning for Human Sensorimotor Controluman model actuated by numerous skeletal muscles, with two human-like eyes whose retinas have spatially nonuniform distributions of photoreceptors. Our prototype sensorimotor system for this model incorporates a set of 20 automatically-trained, deep neural networks (DNNs), half of which are neuromus

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