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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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