Abstract #3125

Multidimensional optimal denoising with block matching is robust to misalignment and contrast changes

Khoi Minh Huynh¹, Sang Hun Chung¹, Yueh Lee¹, and Pew-Thian Yap¹

¹Department of Radiology and Biomedical Research Imaging Center, UNC Chapel Hill, Chapel Hill, NC, United States

Synopsis

Keywords: Data Processing, LungDenoising methods can leverage common information from multiple image volumes for better noise reduction. However, performance can degrade with inter-volume misalignment or contrast changes. We proposed a block-matching denoising method for effective noise removal and robustness to inter-volume differences.

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