Dr. Jian Su
at Mayo Clinic
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Profile Summary

Iterative reconstruction and other noise reduction methods have been employed in CT to improve image
quality and to reduce radiation dose. The non-local means (NLM) filter emerges as a popular choice for
image-based noise reduction in CT. However, the original NLM method cannot incorporate similar structures
if they are in a rotational format, resulting in ineffective denoising in some locations of the image and nonuniform
noise reduction across the image. We have developed a novel rotational-invariant image texture
feature derived from the multiresolutional Stockwell-transform (ST), and applied it to CT image noise
reduction so that similar structures can be identified and fully utilized even when they are in rotated. We
performed a computer simulation study in CT to demonstrate better efficiency in terms of utilizing redundant
information in the image and more uniform noise reduction achieved by ST than by NLM.
Publications (1)

PROCEEDINGS ARTICLE | March 21, 2014
Proc. SPIE. 9034, Medical Imaging 2014: Image Processing
KEYWORDS: Optical filters, Sensors, Image processing, Denoising, Computer simulations, Image analysis, Medical imaging, Image quality, Image filtering, Computed tomography

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