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Abstract #2094

Background tissue suppression for subtractive NCE-MRA techniques based on robust regression using the deviation angle

Hao Li1, Shuo Wang1, Andrew Nicholas Priest2, Martin John Graves2, and David John Lomas1

1Department of Radiology, University of Cambridge, Cambridge, United Kingdom, 2Department of Radiology, Addenbrooke’s Hospital, Cambridge, United Kingdom

Intensity differences of static tissues between bright- and dark-blood images commonly exist in subtractive non-contrast-enhanced MRA techniques, resulting in residual background signal in the subtracted images. Some linear regression models can correct the intensity difference but are sensitive to the large number of blood pixels in thoracic MRA. A robust regression model is developed in this study and is demonstrated to have an effective performance in background suppression for different subtractive NCE-MRA techniques.

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