Graphics processing units (GPUs) are used today in a wide range of applications, mainly
because they can dramatically accelerate parallel computing, are affordable and energy …

Segmentation of anatomical structures, from modalities like computed tomography (CT),
magnetic resonance imaging (MRI) and ultrasound, is a key enabling technology for medical …

Parallel computing has become an important subject in the field of computer science and
has proven to be critical when researching high performance solutions. The evolution of …

Medical imaging currently plays a crucial role throughout the entire clinical applications from
medical scientific research to diagnostics and treatment planning. However, medical …

This paper addresses the application of the extended finite element method (XFEM) to the
modeling of two-dimensional coupled magneto-mechanical field problems. Continuum …

Background 3D segmentation is often a prerequisite for 3D object display and quantitative
measurements. Yet existing voxel-based methods do not directly give information on the …

Purpose: The level‐set method is known to require long computation time for 3D image
segmentation, which limits its usage in clinical workflow. The goal of this study was to …

Purpose: Deep learning (DL) algorithms have shown promising results for brain tumor
segmentation in MRI. However, validation is required prior to routine clinical use. We report …

In this paper we describe a double precision floating point sparse matrix-vector multiplier
(SpMV) and its performance as implemented on a Convey HC-1 reconfigurable computer …

The individuation of areas that are more likely to be impacted by new events in volcanic
regions is of fundamental relevance for mitigating possible consequences, both in terms of …