MRI denoising by nonlocal means on multi-GPU

被引：7

作者：

Granata, Donatella ^{[1
]}

Amato, Umberto ^{[1
]}

Alfano, Bruno ^{[2
]}

机构：

[1] CNR, Ist Applicaz Calcolo Mauro Picone, Naples, Italy

[2] CNR, Ist Biostrutture & Bioimmagini, Naples, Italy

来源：

JOURNAL OF REAL-TIME IMAGE PROCESSING | 2019年 / 16卷 / 02期

关键词：

NonLocal means; Image denoising; Magnetic resonance imaging; Graphical processing unit; IMAGE;

D O I：

10.1007/s11554-016-0566-2

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A critical issue in image restoration is noise removal, whose state-of-art algorithm, NonLocal Means, is highly demanding in terms of computational time. Aim of the present paper is to boost its performance by an efficient algorithm tailored to GPU hardware architectures. This algorithm adapts itself to several variants of the methodologies in terms of different strategies for estimating the involved filtering parameter, type of noise affecting data, multicomponent signals, spatial dimension of the images. Numerical experiments on brain Magnetic Resonance images are provided.

引用

页码：523 / 533

页数：11

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