high performance computing on graphics processing units: hgpu.org

hgpu.org » Tomography

A multi-GPU acceleration for 3D imaging of the prostate

E. A. Attardo, A. Borsic, R. J. Halter

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Tags: CUDA, Medicine, nVidia, Tesla S1070, Tomography, Ultrasound

November 12, 2011 by hgpu

Performance and scalability of Fourier domain optical coherence tomography acceleration using graphics processing units

Jian Li, Pavel Bloch, Jing Xu, Marinko V. Sarunic, Lesley Shannon

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Tags: CUDA, Data acquisition, Medicine, Memory model, nVidia, nVidia GeForce GTX 295, Optics, Tomography

November 6, 2011 by hgpu

True 4D Image Denoising on the GPU

Anders Eklund, Mats Andersson, Hans Knutsson

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Tags: Algorithms, Computational Complexity, Computed tomography, CT, CUDA, FFT, Filtering, Image processing, Medicine, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 580, Tomography

November 3, 2011 by hgpu

Self-calibration of geometric and radiometric parameters for cone-beam computed tomography

Wolfgang Wein, Alexander Ladikos and Armin Baumgartner

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Tags: Algorithms, ATI, ATI Radeon HD 5870, Computed tomography, CT, Image reconstruction, Medicine, nVidia, nVidia GeForce GTX 580, Tomography

October 27, 2011 by hgpu

Mapping Iterative Medical Imaging Algorithm on Cell Accelerator

Meilian Xu, Parimala Thulasiraman

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Tags: Algorithms, Cell processor, Heterogeneous systems, Image processing, Image recognition, Medicine, Optimization, Tomography

October 22, 2011 by hgpu

Denoising Volumetric Data on GPU

Jan Horacek, Jan Kolomaznik, Josef Pelikan, Martin Horak

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Tags: Algorithms, Image processing, Medicine, nVidia, nVidia GeForce 8800 GT, nVidia GeForce GTX 275, nVidia GeForce GTX 460, OpenCL, Signal denoising, Tomography

October 10, 2011 by hgpu

Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs)

W.J. Palenstijna, K.J. Batenburga, J. Sijbersa

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Tags: Biology, Image reconstruction, Medicine, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Tomography

October 8, 2011 by hgpu

GPU-Based Acceleration of the MLEM Algorithm for SPECT Parallel Imaging with Attenuation Correction and Compensation for Detector Response

Akos Szlavecz, Gabor Hesz, Tamas Bukki, Bela Kari, Balazs Benyo

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Tags: Algorithms, Computed tomography, CT, CUDA, Medicine, nVidia, nVidia GeForce GTX 480, Tomography, Visualization

September 25, 2011 by hgpu

Scalable, High Performance Fourier Domain Optical Coherence Tomography: Why FPGAs and Not GPGPUs

Jian Li, Marinko V. Sarunic, Lesley Shannon

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Tags: Algorithms, CUDA, Data acquisition, FPGA, Medicine, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 480, Tomography

September 21, 2011 by hgpu

Parallel Medical Image Reconstruction: From Graphics Processors to Grids

Maraike Schellmann, Sergei Gorlatch, Dominik Meilander, Thomas Kosters, Klaus Schafers, Frank Wubbeling, Martin Burger

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Tags: Algorithms, Cell processor, Grid, Image reconstruction, Medicine, PET, PET scanning, Tomography

September 16, 2011 by hgpu

Fast Monte Carlo Simulation for Patient-specific CT/CBCT Imaging Dose Calculation

Xun Jia, Hao Yan, Xuejun Gu, Steve B. Jiang

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Tags: Computed tomography, CT, CUDA, Heterogeneous systems, Medical Physics, Medicine, Monte Carlo simulation, nVidia, Physics, Tesla C2050, Tomography

September 16, 2011 by hgpu

Interactive volumetric lighting simulating scattering and shadowing

Timo Ropinski, Christian Doring, Christof Rezk-Salama

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Tags: 3D Graphics and Realism, Computed tomography, CT, GLSL, Medicine, nVidia, nVidia GeForce GTX 285, OpenGL, Rendering, Tomography, Ultrasound

September 4, 2011 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

A multi-GPU acceleration for 3D imaging of the prostate

Performance and scalability of Fourier domain optical coherence tomography acceleration using graphics processing units

True 4D Image Denoising on the GPU

Self-calibration of geometric and radiometric parameters for cone-beam computed tomography

Mapping Iterative Medical Imaging Algorithm on Cell Accelerator

Denoising Volumetric Data on GPU

Performance improvements for iterative electron tomography reconstruction using graphics processing units (GPUs)

GPU-Based Acceleration of the MLEM Algorithm for SPECT Parallel Imaging with Attenuation Correction and Compensation for Detector Response

Scalable, High Performance Fourier Domain Optical Coherence Tomography: Why FPGAs and Not GPGPUs

Parallel Medical Image Reconstruction: From Graphics Processors to Grids

Fast Monte Carlo Simulation for Patient-specific CT/CBCT Imaging Dose Calculation

Interactive volumetric lighting simulating scattering and shadowing

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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