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Proposed Approach for OPAL Workflow Sept 2009 Workflow Overview Modules Register orthogonal datasets & Apply transform • Affine registration of sagittal and coronal data to axial data using mutual information (markers not currently used) Resample datasets into new image • Datasets “merged” by resampling • Weighting of each dataset based on distance of point to nearest slice Atlas model creation through expert segmentation • Final model includes volumetric mesh and connected points representing muscle fibers Segmentation by coarse usercontrolled registration (initialization) Segmentation by automated image-based registration Specifications General • Quantify results using – Synthetic data: basic shapes, synthetic med data – Human data: ideal control data, patient data • Prototyped using Matlab unless specified • Module input adaptable to allow for use of Livewire Assumption: Atlas model has corresponding MRI • Alternatives if atlas has no corresponding MRI Future Work 1. Collaboration with Yohann and Marek • Use of their workflow for Mesh-Match-andRepair for patient model segmentation • Contributions to this work: – The deformation of interior nodes, muscles and landmarks (not just surface mesh) – Reliability constraints on landmarks, curves and surfaces Future Work 2. Possible new tongue structure • Surface mesh is arbitrary • Tongue consists of muscle fibers and skin is for visual and collision calculation purposes only, appearing as a “skin” over muscles • Registration deforms the muscle nodes only and ignores visible tongue surface