Joseph V. Hajnal

TL;DR: P positron emission tomography was used to determine the foci of relative cerebral blood flow increases produced when subjects viewed a moving checkerboard pattern, compared to viewing the same pattern when it was stationary.

TL;DR: A framework for reconstructing dynamic sequences of 2-D cardiac magnetic resonance images from undersampled data using a deep cascade of convolutional neural networks (CNNs) to accelerate the data acquisition process is proposed and it is demonstrated that CNNs can learn spatio-temporal correlations efficiently by combining convolution and data sharing approaches.

TL;DR: A practicable procedure is demonstrated that exceeds the accuracy of previous automatic methods and can compete with manual delineations in segmentation propagation and decision fusion of fused brain segmentations.

TL;DR: It is concluded that selecting atlases from large databases for atlas-based brain image segmentation improves the accuracy of the segmentations achieved and shows that image similarity is a suitable selection criterion.

TL;DR: Increased acquisition efficiency has been achieved by exciting several slices simultaneously using the spatial encoding information inherent in a multicoil receiver system and a matrix inversion provides a solution to unfold these images.