Adaptive non-local means filtering based on local noise level for CT denoising

Zhoubo Li; Lifeng Yu; Joshua D. Trzasko; Joel G. Fletcher; Cynthia H. McCollough; Armando Manduca

doi:10.1117/12.913353

8 March 2012 Adaptive non-local means filtering based on local noise level for CT denoising

Zhoubo Li, Lifeng Yu, Joshua D. Trzasko, Joel G. Fletcher, Cynthia H. McCollough, Armando Manduca

Proceedings Volume 8313, Medical Imaging 2012: Physics of Medical Imaging; 83131H (2012) https://doi.org/10.1117/12.913353
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

Radiation dose from CT scans is an increasing health concern in the practice of radiology. Higher dose scans can produce clearer images with high diagnostic quality, but may increase the potential risk of radiation-induced cancer or other side effects. Lowering radiation dose alone generally produces a noisier image and may degrade diagnostic performance. Recently, CT dose reduction based on non-local means (NLM) filtering for noise reduction has yielded promising results. However, traditional NLM denoising operates under the assumption that image noise is spatially uniform noise, while in CT images the noise level varies significantly within and across slices. Therefore, applying NLM filtering to CT data using a global filtering strength cannot achieve optimal denoising performance. In this work, we have developed a technique for efficiently estimating the local noise level for CT images, and have modified the NLM algorithm to adapt to local variations in noise level. The local noise level estimation technique matches the true noise distribution determined from multiple repetitive scans of a phantom object very well. The modified NLM algorithm provides more effective denoising of CT data throughout a volume, and may allow significant lowering of radiation dose. Both the noise map calculation and the adaptive NLM filtering can be performed in times that allow integration with the clinical workflow.

Citation Download Citation

Zhoubo Li, Lifeng Yu, Joshua D. Trzasko, Joel G. Fletcher, Cynthia H. McCollough, and Armando Manduca "Adaptive non-local means filtering based on local noise level for CT denoising", Proc. SPIE 8313, Medical Imaging 2012: Physics of Medical Imaging, 83131H (8 March 2012); https://doi.org/10.1117/12.913353

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available