Abstract #2548

Noise reduction with TGV, Gaussian and Wiener filtering methods in FLAIR² images

René Schranzer¹, Alexander Rauscher², Evelin Haimburger¹, Kristian Bredies³, Gernot Reishofer⁴, and Günther Grabner^1,5

¹Department of Radiologic Technology, Carinthia University of Applied Sciences, Klagenfurt, Austria, ²UBC MRI Research Centre, University of British Columbia, Vancouver, Canada, ³Institute for Mathematics and Scientific Computing, University of Graz, Graz, Austria, ⁴Department of Radiology, Medical University of Graz, Graz, Austria, ⁵Institute for Applied Research on Ageing, Carinthia University of Applied Sciences, Klagenfurt, Austria

The reduction of noise is of high value for FLAIR² images because the multiplication of FLAIR and T2 images will always result in an image with a reduced Signal-to-noise-ratio. Here different filter methods, like Gaussian, Wiener and Total Generalized Variation were used to demonstrate noise reduction. The drawback of noise reduction is a blurring effect of anatomical structures. In this study we demonstrate that TGV filtering has certain advantages compared to Wiener and Gaussian techniques in research and clinical applications.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.