high performance computing on graphics processing units: hgpu.org

hgpu.org » Image reconstruction

How GPUs Can Improve the Quality of Magnetic Resonance Imaging

Sam S. Stone, Haoran Yi, Justin P. Haldar, Wen-mei W. Hwu, Bradley P. Sutton, and Zhi-Pei Liang

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Tags: CUDA, FFT, Image processing, Image reconstruction, Magnetic resonance imaging, Medicine, MRI, nVidia, nVidia GeForce 8800 GTX

February 20, 2011 by hgpu

Using Graphics Processors to Accelerate Synthetic Aperture Sonar Imaging via Backpropagation

Daniel P. Campbell, Daniel A. Cook

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Tags: CUDA, Image reconstruction, nVidia, Physics, Tesla S1070

February 16, 2011 by hgpu

3D tumor localization through real-time volumetric x-ray imaging for lung cancer radiotherapy

Ruijiang Li, John H. Lewis, Xun Jia, Xuejun Gu, Michael Folkerts, Chunhua Men, William Y. Song, Steve B. Jiang

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Tags: CUDA, Image reconstruction, Medical Physics, Medicine, nVidia, Physics, Radiotherapy, Tesla C1060

February 9, 2011 by hgpu

Focused Volumetric Visual Hull with Color Extraction

Daniel Knoblauch, Falko Kuester

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Tags: Algorithms, Computer science, CUDA, Image reconstruction, nVidia, nVidia GeForce 8800 GTX

February 6, 2011 by hgpu

Sparse regularization in MRI iterative reconstruction using GPUs

Yue Zhuo, Bradley Sutton, Xiao-Long Wu, Justin Haldar, Wen-mei Hwu, Zhipei Liang

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Tags: CUDA, Image processing, Image reconstruction, MRI, nVidia, nVidia GeForce GTX 280, Sparse matrix

January 24, 2011 by hgpu

Multi-GPU Implementation for Iterative MR Image Reconstruction with Field Correction

Y. Zhuo, X-L. Wu, J. P. Haldar, W-M. W. Hwu, Z-P. Liang, and B. P. Sutton

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Tags: CUDA, Image processing, Image reconstruction, MRI, nVidia, Tesla S1070

January 24, 2011 by hgpu

Accelerating iterative field-compensated MR image reconstruction on GPUs

Yue Zhuo, Xiao-Long Wu, Justin P. Haldar, Wen-mei Hwu, Zhi-pei Liang, Bradley P. Sutton

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Tags: Conjugate gradient solver, CUDA, Image processing, Image reconstruction, Medicine, MRI, nVidia, nVidia GeForce GTX 280

January 24, 2011 by hgpu

Compensated Visual Hull for Defective Segmentation and Occlusion

Hansung Kim, Ryuuki Sakamoto, Itaru Kitahara, Neal Orman, Tomoji Toriyama, Kiyoshi Kogure

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Tags: Computer science, Computer vision, Image reconstruction, nVidia, nVidia GeForce 8800 GTS, Shaders

January 12, 2011 by hgpu

Fully-3D GPU PET reconstruction

J. L. Herrai, S. Espana, J. Cal-Gonzalez, J. J. Vaquero, M. Desco, J. M. Udias

Tags: Computed tomography, CT, Image processing, Image reconstruction, Medicine

January 6, 2011 by hgpu

Single-particle 3D reconstruction from cryo-electron microscopy images on GPU

Guangming Tan, Ziyu Guo, Mingyu Chen, Dan Meng

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Tags: CUDA, Electron microscopy, Image processing, Image reconstruction, Medicine, nVidia, nVidia GeForce 8800 GTX

December 29, 2010 by hgpu

Multi GPU Implementation of Iterative Tomographic Reconstruction Algorithms

Byunghyun Jang, David R. Kaeli, Synho Do, Homer Pien

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Tags: Computed tomography, CT, CUDA, GPU cluster, Image processing, Image reconstruction, Medicine, nVidia, Tesla S870

December 26, 2010 by hgpu

Parallel High Resolution Real-time Visual Hull On GPU

Wolfgang Waizenegger, Ingo Feldmann, Peter Eisert, Peter Kauff

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Tags: Computer science, CUDA, Image reconstruction, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 280, Real-time graphics

December 26, 2010 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

How GPUs Can Improve the Quality of Magnetic Resonance Imaging

Using Graphics Processors to Accelerate Synthetic Aperture Sonar Imaging via Backpropagation

3D tumor localization through real-time volumetric x-ray imaging for lung cancer radiotherapy

Focused Volumetric Visual Hull with Color Extraction

Sparse regularization in MRI iterative reconstruction using GPUs

Multi-GPU Implementation for Iterative MR Image Reconstruction with Field Correction

Accelerating iterative field-compensated MR image reconstruction on GPUs

Compensated Visual Hull for Defective Segmentation and Occlusion

Fully-3D GPU PET reconstruction

Single-particle 3D reconstruction from cryo-electron microscopy images on GPU

Multi GPU Implementation of Iterative Tomographic Reconstruction Algorithms

Parallel High Resolution Real-time Visual Hull On GPU

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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