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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