MEDICAL IMAGE DENOISING USING KERNEL RIDGE REGRESSION

被引：0

作者：

Dinh Hoan Trinh ^{[1
]}

Luong, Marie ^{[2
]}

Rocchisani, Jean-Marie ^{[3
]}

Canh Duong Pham ^{[4
]}

Dibos, Francoise ^{[1
]}

机构：

[1] Univ Paris 13, LAGA, 99 Ave Jean Baptiste Clement, F-93430 Villetaneuse, France

[2] Univ Paris 13, L2TI, Villetaneuse, France

[3] Hop Avicenne Med Nucl, Bobigny, France

[4] Vietnam Acad Sci & Technol, CIID, Hanoi, Vietnam

来源：

2011 18TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2011年

关键词：

Nonlinear regression; Medical image denoising; Kernel Ridge Regression; CT image; MRI image;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Medical images are often corrupted by random noise, leading to undesirable visual quality. Thus, image denoising is one of the fundamental tasks required by medical imaging analysis. In this paper, we propose a novel learning method for the reduction of Gaussian noise of Computed Tomography (CT) image and Rician noise of Magnetic Resonance Imaging (MRI) image based on a given set of standard images and the Kernel Ridge Regression (KRR). Experimental results demonstrate the outperformance of the proposed technique over various other methods in terms of both objective and subjective evaluations.

引用

页码：1597 / 1600

页数：4

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