Abstract #3756
Image Hessian based Automatic Cranium Segmentation for Blackbone and Silenz MRI
Max W.K. Law 1 , Jing Yuan 1 , Gladys G. Lo 2 , Oi Lei Wong 1 , Abby Y. Ding 1 , and Siu Ki Yu 1
1
Medical Physics and Research Department,
Hong Kong Sanatorium & Hospital, Hong Kong, Hong Kong,
2
Department
of Diagnostic and Interventional Radiology, Hong Kong
Sanatorium & Hospital, Hong Kong, Hong Kong
This work describes a new algorithm that automatically
segments the cranium from two MRI sequences - gradient
echo based "Blackbone" MRI and Ultra-short-TE "Silenz"
MRI. This algorithm deforms an ellipsoid template
according to the Hessian based image statistics, to find
the boundaries where abrupt intensity changes are
observed. We also studied the bone thickness consistency
and bone signal contrast compared to the neighboring
tissues for these two sequences. This method is
potentially helpful for clinical applications such as
MR-based cephalometry and radiotherapy planning to
reduce or eliminate radiation deposition in patients.
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