With the advent of multi-core processors, desktop application developers must finally face parallel computing and its challenges. A large portion of the computational load in a p...
We present a new data partitioning strategy for parallel computing on three interconnected clusters. This partitioning has two advantages over existing partitionings. First it can...
Topology-preserving geometric deformable models (TGDMs) are used to segment objects that have a known topology. Their accuracy is inherently limited, however, by the resolution of...
Training convolutional neural networks (CNNs) on large sets of high-resolution images is too computationally intense to be performed on commodity CPUs. Such architectures however ...
In this paper, we propose an inherent parallel scheme for 3D image segmentation of large volume data on a GPU cluster. This method originates from an extended Lattice Boltzmann Mod...