Digital Breast Tomosynthesis (DBT) is a technology that creates three dimensional (3D) images of breast tissue. Tomosynthesis mammography detects lesions that are not detectable with other imaging systems. If image reconstruction time is in the order of seconds, we can use Tomosynthesis systems to perform Tomosynthesis-guided Interventional procedures. This research has been designed to study u...

among different discretization approaches, finite difference method (fdm) is widely used for acoustic and elastic full-wave form modeling. an inevitable deficit of the technique, however, is its sever requirement to computational resources. a promising solution is parallelization, where the problem is broken into several segments, and the calculations are distributed over different processors. ...

normal 0 false false false en-us x-none ar-sa digital breast tomosynthesis (dbt) is a technology that creates three dimensional (3d) images of breast tissue. tomosynthesis mammography detects lesions that are not detectable with other imaging systems. if image reconstruction time is in the order of seconds, we can use tomosynthesis systems to perform tomosynthesis-guided interventional procedur...

A finite-difference Micromagnetic simulation code in MATLAB is presented with Graphics Processing Unit (GPU) acceleration. The high performance of Graphics Processing Unit (GPU) is demonstrated compared to a typical Central Processing Unit (CPU) based code. The speed-up of GPU to CPU is shown to be greater than 30 for problems with larger sizes on a mid-end GPU in single precision. The code is ...

There are different variants of Particle Swarm Optimization (PSO) algorithm such as Adaptive Particle Swarm Optimization (APSO) and Particle Swarm Optimization with an Aging Leader and Challengers (ALC-PSO). These algorithms improve the performance of PSO in terms of finding the best solution and accelerating the convergence speed. However, these algorithms are computationally intensive. The go...

A micromagnetic simulator running on graphics processing unit (GPU) is presented. It achieves significant performance boost as compared to previous central processing unit (CPU) simulators, up to two orders of magnitude for large input problems. Different from GPU implementations of other research groups, this simulator is developed with C++ Accelerated Massive Parallelism (C++ AMP) and is hard...