Automatic brain segmentation using fractional signal modeling of a multiple flip angle, spoiled gradient-recalled echo acquisition

作者：Ahlgren Andre^*; Wirestam Ronnie; Stahlberg Freddy; Knutsson Linda

来源：Magnetic Resonance Materials in Physics Biology and Medicine, 2014, 27(6): 551-565.

DOI：10.1007/s10334-014-0439-2

• Brain segmentation
• Partial volume estimation
• T1 mapping
• SPGR
• VFA
• FRASIER

The aim of this study was to demonstrate a new automatic brain segmentation method in magnetic resonance imaging (MRI). %26lt;br%26gt;The signal of a spoiled gradient-recalled echo (SPGR) sequence acquired with multiple flip angles was used to map T1, and a subsequent fit of a multi-compartment model yielded parametric maps of partial volume estimates of the different compartments. The performance of the proposed method was assessed through simulations as well as in-vivo experiments in five healthy volunteers. %26lt;br%26gt;Simulations indicated that the proposed method was capable of producing robust segmentation maps with good reliability. Mean bias was below 3 % for all tissue types, and the corresponding similarity index (Dice%26apos;s coefficient) was over 95 % (SNR = 100). In-vivo experiments yielded realistic segmentation maps, with comparable quality to results obtained with an established segmentation method. Relative whole-brain cerebrospinal fluid, grey matter, and white matter volumes were (mean +/- A SE) respectively 6.8 +/- A 0.5, 47.3 +/- A 1.1, and 45.9 +/- A 1.3 % for the proposed method, and 7.5 +/- A 0.6, 46.2 +/- A 1.2, and 46.3 +/- A 0.9 % for the reference method. %26lt;br%26gt;The proposed approach is promising for brain segmentation and partial volume estimation. The straightforward implementation of the method is attractive, and protocols that already rely on SPGR-based T1 mapping may employ this method without additional scans.

• 出版日期2014-12