State-Based Gauss-Seidel Framework for Real-time 2D Ultrasound Image Sequence Denoising on GPUs

Dolwithayakul, Banpot; Chantrapornchai, Chantana; Chumchob, Noppadol

doi:10.14257/ijmue.2014.9.1.04

Cited by 10 publications

(4 citation statements)

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“…Surveys by Eklunf et al [24] and Chen et al [25] provide a summary of GPU-based processing of general and medical images. Other recent methods have been developed for denoising MRI data [26], [27], CT data [28], [29], X-ray data [30], 2D ultrasound images [31], and 3D ultrasound images [32].…”

Section: Related Workmentioning

confidence: 99%

GPU-based Method for Denoising Time Series of Fluorescent Imaging Data

pelic

Lukač

alik

2014

2014 Second International Symposium on Computing and Networking

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This paper presents a GPU-based method for denoising of time series images obtained by confocal microscopy, in order to study the oscillations of calcium and membrane voltage potential in beta cells. Since denoising of captured images is one of the first crucial steps, it is desirable that it is highly efficient and fast. This is especially important when dealing with a large number of time series images, where the computational complexity increases tremendously. Results demonstrate that the proposed method is at least 5 times faster, in comparison with a CPU-based implementation, while retaining the same accuracy.

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Section: Related Workmentioning

confidence: 99%

GPU-based Method for Denoising Time Series of Fluorescent Imaging Data

pelic

Lukač

alik

2014

2014 Second International Symposium on Computing and Networking

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“…And this causes in unpredictable and unwanted deformities, especially in uniform areas of even slightly noisy images. In addition, unsharp masking process can overimproves high contrast areas, and eventually images are not well showed [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

Masking-based Reinforced Edges for Blur Images

Jeon

2015

IJSEIA

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“…The speckle noise or periodic noise can be removed in frequency domain by using band reject filtering or notch filtering [11][12][13]. Among them, the median filtering method has been the most widely used for denoising noisy images [14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%