文件列表:

LICENSE.txt (1086, 2018-12-13)
Wave3D (0, 2018-12-13)
Wave3D\FSfarras.m (1287, 2018-12-13)
Wave3D\afb3D.m (2683, 2018-12-13)
Wave3D\cshift3D.m (634, 2018-12-13)
Wave3D\dwt3D.m (659, 2018-12-13)
Wave3D\dwt3D_plots.m (722, 2018-12-13)
Wave3D\farras.m (994, 2018-12-13)
Wave3D\idwt3D.m (433, 2018-12-13)
Wave3D\mixingsubband.m (1481, 2018-12-13)
Wave3D\pm4.m (270, 2018-12-13)
Wave3D\pm4inv.m (277, 2018-12-13)
Wave3D\sfb3D.m (1647, 2018-12-13)
demos (0, 2018-12-13)
demos\data.mat (3779759, 2018-12-13)
demos\demo_MCdenoising.m (1548, 2018-12-13)
demos\demo_basic.m (4565, 2018-12-13)
demos\demo_mcx_anlm.m (2745, 2018-12-13)
src (0, 2018-12-13)
src\ANLMGPU.cpp (7328, 2018-12-13)
src\Makefile (3017, 2018-12-13)
src\filterGPU.cu (32170, 2018-12-13)
src\filterGPU.h (1989, 2018-12-13)
src\filterGPU_s.cu (29005, 2018-12-13)
src\filterGPU_v.cu (31615, 2018-12-13)
src\ganlm.m (1473, 2018-12-13)

--------------------------------------------------------------------- GPU-accelerated adaptive non-local means filter --------------------------------------------------------------------- Copyright (c) 2018 Yaoshen Yuan, Qianqian Fang --------------------------------------------------------------------- Author: Yaoshen Yuan and Qianqian Fang Webpage: http://mcx.space Contact: yuan.yaos at husky.neu.edu q.fang at neu.edu Publication: Yaoshen Yuan, Leiming Yu, Zafer Dogan, and Qianqian Fang, "Graphics processing units-accelerated adaptive nonlocal means filter for denoising three-dimensional Monte Carlo photon transport simulations," J. of Biomedical Optics, 23(12), 121618 (2018). https://doi.org/10.1117/1.JBO.23.12.121618 == Contents == \src --ANLMGPU.c --filterGPU.h --filterGPU.cu --filterGPU_v.cu --filterGPU_s.cu --Makefile \bin --ganlm.mexa*** \demo --demo_basic.m --demo_MCdenoising.m --data.mat \Wave3D README.txt LICENSE.txt == Introduction == The Monte Carlo (MC) photon transport is the gold standard for modeling light propagation inside turbid media. However, the inherent stochastic noise becomes dominant when using less photons or in the region far away from the source. Instead of lauching more photons, we can apply denoising technique to achieve results equivalent to lauching more photons. This software takes advantage of the adaptive non-local means (ANLM) filter [2] for its adaptivity to spatially varying noise to denoise the shot noise in the MC images while having a good edge preservation. However, the original CPU version is less beneficial for MC images due to its long run-time. This work therefore optimized the speed using GPU. In a previous work [3], a GPU version of ANLM filter was implemented but there are some simplifications and a few features missing. The comparison can be seen below. _____________________________________________________________________ Main Features CPU-ANLM GPU-ANLM this work --------------------------------------------------------------------- Compute type CPU GPU GPU Data type* double short integer float Block-wise update yes no no Non-local patch pre-selection yes no yes Adaptive to noise 3D 2D 3D Filtering Gaussian yes yes yes Filtering Rician yes yes yes Sub-band mixing yes no yes GPU block - 16x16x1 8x8x8 GPU texture memory - no yes Source code open-source closed-source open-source _____________________________________________________________________ Furthermore, this software can be not only used for MC images, but also for denoising other volumetric images as the MR or CT 3D scans. == References == If you use this filter in your research, the author of this software would like you to cite the below paper in your related publications [1]. [1] Yuan Y, Yu L, Dogan Z, Fang Q. Graphics processing units-accelerated adaptive nonlocal means filter for denoising three-dimensional Monte Carlo photon transport simulations. Journal of Biomedical Optics. 2018 Nov; 23(12): 121618. In addition, other publications relevant to Monte Carlo photon transport and adaptive non-local means filter can be found below. [2] Manjon J V, Coupe P, Marti‐Bonmati L, et al. "Adaptive non‐local means denoising of MR images with spatially varying noise levels," Journal of Magnetic Resonance Imaging, 2010, 31(1): 192-203. [3] Granata D, Amato U, Alfano B. "MRI denoising by nonlocal means on multi-GPU," Journal of Real-Time Image Processing, 2016: 1-11. [4] Fang Q, Boas D A. "Monte Carlo simulation of photon migration in 3D turbid media accelerated by graphics processing units," Optics express, 2009, 17(22): 20178-20190.

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