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Abstract #0340

Automatic Brain Segmentation using Fractional Signal Modelling of a Multiple Flip-Angle Spoiled Gradient-Recalled Echo Acquisition

Andr Ahlgren 1 , Ronnie Wirestam 1 , Freddy Sthlberg 1,2 , and Linda Knutsson 1

1 Department of Medical Radiation Physics, Lund University, Lund, Sweden, 2 Department of Diagnostic Radiology, Lund University, Lund, Sweden

Brain segmentation based on multi-component modelling of quantitative MRI data has yielded great interest recently. Those methods are attractive due to their simplicity in modelling and processing. In this work, we present a novel method to segment gray matter, white matter, and cerebrospinal fluid, based on a spoiled gradient-recalled echo (SPGR) sequence acquired with varying flip angles (VFA). The method, dubbed SPGR-SEG, yielded robust and realistic segmentation maps in good agreement with a reference method based on inversion recovery data.

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