Improving SNR in Susceptibility Weighted Imaging by a NLM-based denoising scheme

P. Borrelli, E. Tedeschi, S. Cocozza, C. Russo, M. Salvatore, G. Palma, M. Comerci, B. Alfano, E. M. Haacke

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The combination of magnitude and phase information inherent in Susceptibility-Weighted Imaging (SWI) greatly benefits from high-resolution MRI acquisitions. The application of a denoising filter to produce SWI images with higher signal-to-noise ratio (SNR) while preserving small structures from excessive blurring is therefore extremely desirable, but non-trivial, as the distribution of magnitude and phase noise may introduce biases during image restoration. Here we present a new dedicated noise removal algorithm based on the Non-Local Means (NLM) filter and compare its results with the original SWI and 'standard' NLM-denoised human brain images. Both the visual assessment by two expert readers and the quantitative evaluation of the contrast changes of the voxel intensities demonstrated that the images restored with the proposed algorithm fared consistently better than the other two schemes, showing that a proper handling of noise in the complex MRI dataset may lead to visible improvements of the overall SWI quality.

Original languageEnglish
Title of host publicationIST 2014 - 2014 IEEE International Conference on Imaging Systems and Techniques, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages346-350
Number of pages5
ISBN (Print)9781479967483
DOIs
Publication statusPublished - Nov 14 2014
Event2014 IEEE International Conference on Imaging Systems and Techniques, IST 2014 - Santorini Island, Greece
Duration: Oct 14 2014Oct 17 2014

Other

Other2014 IEEE International Conference on Imaging Systems and Techniques, IST 2014
CountryGreece
CitySantorini Island
Period10/14/1410/17/14

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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    Borrelli, P., Tedeschi, E., Cocozza, S., Russo, C., Salvatore, M., Palma, G., Comerci, M., Alfano, B., & Haacke, E. M. (2014). Improving SNR in Susceptibility Weighted Imaging by a NLM-based denoising scheme. In IST 2014 - 2014 IEEE International Conference on Imaging Systems and Techniques, Proceedings (pp. 346-350). [6958502] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IST.2014.6958502