In magnetic resonance imaging (MRI), data averaging is often used to improve signal-to-noise ratio (SNR) of the images. However, image blurring can be induced by averaging if movements occur during scanning. Inspired by the patch-matching method used in the non-local means algorithm, a new method to find out local offsets of structures in multiple images was proposed by comparing the neighborhood similarities of the image patches. The local offsets could then be corrected before weighted averaging of the images. The performance of the proposed method was verified with both phantom and patient images. The results demonstrated that the proposed algorithm could improve SNR while preserving the image edges and details correctly.
XIE Hai-bin
,
ZHOU Min-xiong
,
XIANG Zhi-ming
,
LI Wen-jing
,
YAN Xu
,
YANG Guang
. Magnetic Resonance Image Averaging with Local Offset Correction[J]. Chinese Journal of Magnetic Resonance, 2017
, 34(3)
: 294
-301
.
DOI: 10.11938/cjmr20162525
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