Abstract #1915

Automatic MR-based Skull Segmentation using Local Shape and Global Topology Priors

Max W.K. Law¹, Calvin M.H. Lee¹, Gladys G. Lo², Jing Yuan¹, Oilei Wong¹, Abby Y. Ding¹, and Siu Ki Yu¹

¹Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, Hong Kong, ²Department of Diagnostic and Interventional Radiology, Hong Kong Sanatorium & Hospital, Hong Kong, Hong Kong

This abstract proposes a new algorithm that automatically segments the skull from gradient echo based magnetic resonance images to facilitate MR-based radiotherapy planning. The proposed algorithm compared the neighboring voxel intensity to capture local structural information of bone. The structural information was incorporated in a topology template which encapsulated global topology prior of skulls to achieve automatic segmentation. With the sequence-independent structural and topology priors, this method is potentially applicable to other scanning sequences. The segmented skull will be helpful for clinical applications such as cephalometry and MR-based radiotherapy planning to reduce ionizing-radiation received by patients.

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