Adaptive Nonlocal Means Method for Denoising Basis Material Images From Dual-Energy Computed Tomography.

Abstract:

:We propose an adaptive nonlocal means approach for image-domain material decomposition in low-dose dual-energy micro-computed tomography. The key idea is to create a distribution map for decomposition error and assign a smooth weight for a given pixel. This method is applied to the decomposed images of 3 basis materials: bone, soft tissue, and gold in our applications. We assume that bone and gold cannot coexist in the same pixel and regroup these basis materials into 2 categories. For soft tissue, the proposed algorithm is implemented in a noniterative mode. For bone and gold, an iterative mode is used and followed by a postiteration process. Both our numerical simulation and in vivo preclinical experiment results show that the proposed adaptive nonlocal means outperforms other state-of-the-art denoising algorithms, such as the original nonlocal means and total variation minimization methods.

journal_name

J Comput Assist Tomogr

authors

Yuan Y,Zhang Y,Yu H

doi

10.1097/RCT.0000000000000805

subject

Has Abstract

pub_date

2018-11-01 00:00:00

pages

972-981

issue

6

eissn

0363-8715

issn

1532-3145

journal_volume

42

pub_type

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