Inverse technique for combined model and sparse data estimates of brain motion

Karen E. Lunn; Keith D. Paulsen; David W. Roberts; Francis E. Kennedy; Alex Hartov

doi:10.1117/12.479720

30 May 2003 Inverse technique for combined model and sparse data estimates of brain motion

Karen E. Lunn, Keith D. Paulsen, David W. Roberts, Francis E. Kennedy, Alex Hartov

Proceedings Volume 5029, Medical Imaging 2003: Visualization, Image-Guided Procedures, and Display; (2003) https://doi.org/10.1117/12.479720
Event: Medical Imaging 2003, 2003, San Diego, California, United States

Abstract

Model-based approaches to correct for brain shift in image-guided neurosurgery systems have shown promising results. Despite the initial success of such methods, the complex mechanical behavior of the brain under surgical loads makes it likely that model predictions could be improved with the incorporation of real-time measurements of tissue shift in the OR. To this end, an inverse method has been developed using sparse data and model constraints to generate estimates of brain motion. Based on methodology from ocean circulation modeling, this computational scheme combines estimates of statistical error in forcing conditions with a least squares minimization of the model-data misfit to directly estimate the full displacement solution. The method is tested on a 2D simulation based on clinical data in which ultrasound images were co-registered to the preoperative MR stack. Calculations from the 2D forward model are used as the 'gold standard' to which the inverse scheme is compared. Initial results are promising, though further study is needed to ascertain its value in 3D shift estimates.

Citation Download Citation

Karen E. Lunn, Keith D. Paulsen, David W. Roberts, Francis E. Kennedy, and Alex Hartov "Inverse technique for combined model and sparse data estimates of brain motion", Proc. SPIE 5029, Medical Imaging 2003: Visualization, Image-Guided Procedures, and Display, (30 May 2003); https://doi.org/10.1117/12.479720

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