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22 March 2007 A surface misfit inversion method for brain deformation modeling
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Biomechanical models of brain deformation are useful tools for estimating the shift that occurs during neurosurgical interventions. Incorporation of intra-operative data into the biomechanical model improves the accuracy of the registration between the patient and the image volume. The representer method to solve the adjoint equations (AEM) for data assimilation has been developed. In order to improve the computational efficiency and to process more intraoperative data, we modified the adjoint equation method by changing the way in which intraoperative data is applied. The current formulation is developed around a point-based data-model misfit. Surface based data-model misfit could be a more robust and computationally efficient technique. Our approach is to express the surface misfit as the volume between the measured surface and model predicted surface. An iterative method is used to solve the adjoint equations. The surface misfit criterion is tested in a cortical distension clinical case and compared to the results generated with the prior point-based methodology solved either iteratively or with the representer algorithm. The results show that solving the adjoint equations with an iterative method improves computational efficiency dramatically over the representer approach and that reformulating the minimization criterion in terms of a surface description is even more efficient. Applying intra-operative data in the form of a surface misfit is computationally very efficient and appears promising with respect to its accuracy in estimating brain deformation.
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Fenghong Liu, Keith D. Paulsen, Alexander Hartov, and David W. Roberts "A surface misfit inversion method for brain deformation modeling", Proc. SPIE 6509, Medical Imaging 2007: Visualization and Image-Guided Procedures, 65092L (22 March 2007); doi: 10.1117/12.710234;

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