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Med Image Comput Comput Assist Interv. 2017 Sep;10433:92-99. doi: 10.1007/978-3-319-66182-7_11. Epub 2017 Sep 4.

Falx Cerebri Segmentation via Multi-atlas Boundary Fusion.

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Dept. of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Dept. of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA.
CNRM, Henry Jackson Foundation, Bethesda, MD 20817, USA.
Radiology and Imaging Sciences, NIH, Bethesda, MD 20892, USA.


The falx cerebri is a meningeal projection of dura in the brain, separating the cerebral hemispheres. It has stiffer mechanical properties than surrounding tissue and must be accurately segmented for building computational models of traumatic brain injury. In this work, we propose a method to segment the falx using T1-weighted magnetic resonance images (MRI) and susceptibility-weighted MRI (SWI). Multi-atlas whole brain segmentation is performed using the T1-weighted MRI and the gray matter cerebrum labels are extended into the longitudinal fissure using fast marching to find an initial estimate of the falx. To correct the falx boundaries, we register and then deform a set of SWI with manually delineated falx boundaries into the subject space. The continuous-STAPLE algorithm fuses sets of corresponding points to produce an estimate of the corrected falx boundary. Correspondence between points on the deformed falx boundaries is obtained using coherent point drift. We compare our method to manual ground truth, a multi-atlas approach without correction, and single-atlas approaches.


Falx cerebri; MRI; boundary fusion; segmentation

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