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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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