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Frameworks in Medical Image Analysis with Deep Neural Networks

Dominik Müller

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Tags: Computed tomography, CT, Deep learning, Image processing, Medicine, Microscopy, Neural networks, nVidia, nVidia Titan RTX, Package, Python, Thesis, Tomography

November 27, 2023 by hgpu

OpenCL FPGA Optimization guided by memory accesses and roofline model analysis applied to tomography acceleration

Daouda Diakite, Nicolas Gac, Maxime Martelli

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Tags: Computed tomography, Computer science, CT, FPGA, HLS, Medicine, OpenCL, Tomography

July 18, 2021 by hgpu

Low-complexity Distributed Tomographic Backprojection for large datasets

Gilberto Martinez Jr., Janito V. Ferreira Filho, Eduardo X. Miqueles

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 740 M, nVidia GeForce GTX X, nVidia Tegra TX1, Package, Tomography

April 30, 2017 by hgpu

BioEM: GPU-accelerated computing of Bayesian inference of electron microscopy images

Pilar Cossio, David Rohr, Fabio Baruffa, Markus Rampp, Volker Lindenstruth, Gerhard Hummer

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Tags: Bayesian, Biology, Biomolecules, CUDA, Electron microscopy, Heterogeneous systems, Medicine, Microscopy, MPI, nVidia, nVidia GeForce GTX Titan, OpenMP, Package, Tesla K20, Tomography

October 8, 2016 by hgpu

GPU-accelerated adjoint algorithmic differentiation

Felix Gremse, Andreas Hofter, Lukas Razik, Fabian Kiessling, Uwe Naumann

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Tags: Algorithms, Computer science, CUDA, Image reconstruction, nVidia, nVidia GeForce GTX Titan Black, Tomography

November 20, 2015 by hgpu

Parallelization of DIRA and CTmod using OpenMP and OpenCL

Alexander Ortenberg

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Tags: AMD Radeon R7 260, ATI, Computed tomography, CT, Image processing, Image reconstruction, Intel Xeon Phi, Medicine, OpenCL, OpenMP, Thesis, Tomography

June 16, 2015 by hgpu

Deep convolutional networks for pancreas segmentation in CT imaging

Holger R. Roth, Amal Farag, Le Lu, Evrim B. Turkbey, Ronald M. Summers

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Tags: Computed tomography, CT, CUDA, Deep learning, Medicine, Neural networks, nVidia, nVidia GeForce GTX Titan Z, Tomography

April 17, 2015 by hgpu

High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study

Gloria Ortega Lopez

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Tags: Computer science, CUDA, Differential equations, FEM, Finite difference, Finite element method, GPU cluster, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Package, Partial differential equations, PDEs, Sparse matrix, Tesla C2050, Tesla M2070, Tesla M2090, Thesis, Tomography

March 30, 2015 by hgpu

A fast marching method based back projection algorithm for photoacoustic tomography in heterogeneous media

Tianren Wang, Yun Jing

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Tags: CUDA, Heterogeneous systems, Image reconstruction, Medical Physics, Medicine, nVidia, Physics, Tesla C2075, Tomography

January 19, 2015 by hgpu

The Use of GPUs for Solving the Computed Tomography Problem

A.E. Kovtanyuk

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Tags: Computed tomography, CT, CUDA, Image processing, nVidia, nVidia GeForce GTX 660 M, nVidia GeForce GTX 690, Tomography

July 17, 2014 by hgpu

GPU/CPU Parallel Computation of Material Damage

Jie Shen, Diego Vela, Ankita Singh, Kexing Song, Guoshang Zhang, Bradon LaFreniere, Hao Chen

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Tags: CAD, Computed tomography, CT, CUDA, Materials Science, nVidia, nVidia Quadro FX 1700, Tesla C1060, Tomography

June 19, 2014 by hgpu

High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System

Manob Jyoti Saikia, Rajan Kanhirodan, Ram Mohan Vasu

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Tags: CUDA, FEM, Finite element method, Image processing, Medicine, nVidia, Tesla K20, Tomography

June 6, 2014 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

Frameworks in Medical Image Analysis with Deep Neural Networks

OpenCL FPGA Optimization guided by memory accesses and roofline model analysis applied to tomography acceleration

Low-complexity Distributed Tomographic Backprojection for large datasets

BioEM: GPU-accelerated computing of Bayesian inference of electron microscopy images

GPU-accelerated adjoint algorithmic differentiation

Parallelization of DIRA and CTmod using OpenMP and OpenCL

Deep convolutional networks for pancreas segmentation in CT imaging

High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study

A fast marching method based back projection algorithm for photoacoustic tomography in heterogeneous media

The Use of GPUs for Solving the Computed Tomography Problem

GPU/CPU Parallel Computation of Material Damage

High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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