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Abstract #3025

A 3D Slicer Extension for Retrospective MP2RAGE Background Suppression

Henry Braun1, Samuel Brenny1, Rémi Patriat1, Tara Palnitkar1, Jayashree Chandrasekaran1, Karianne Sretavan Wong1,2, and Noam Harel1,3
1Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States, 2Neuroscience, University of Minnesota, Minneapolis, MN, United States, 3Neurology, University of Minnesota, Minneapolis, MN, United States

Synopsis

Keywords: Data Processing, Data Processing

Motivation: MP2RAGE provides enhanced T1-weighted images but contains high-amplitude noise in areas of low signal. This can cause processing pipelines developed for traditional T1 images to fail. A “denoising” algorithm exists, but requires complex-valued image data which are not available retrospectively.

Goal(s): Provide an algorithm and easy-to-use interface for eliminating MP2RAGE background noise using only available scanner outputs.

Approach: We have developed a 3D Slicer extension for performing noise suppression with only the available MP2RAGE and inversion magnitude images.

Results: Our method generates background-suppressed and artifact-free images. The program was tested and optimized to be used with the HCP structural pipeline.

Impact: Here, we present a fast easy-to-use 3D Slicer extension for suppressing background noise in MP2RAGE images. It requires no extra phase data, enables users to reprocess already acquired images, and encourages the adoption of MP2RAGE as a primary T1-weighted acquisition.

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Keywords