Biomechanical Model as a Registration Tool for Image-Guided Neurosurgery: Evaluation Against BSpline Registration |
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Authors: | Ahmed Mostayed Revanth Reddy Garlapati Grand Roman Joldes Adam Wittek Aditi Roy Ron Kikinis Simon K Warfield Karol Miller |
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Institution: | 1. Intelligent Systems for Medicine Laboratory, The University of Western Australia, Perth, Australia 2. Surgical Planning Laboratory, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA 3. Computational Radiology Laboratory, Children’s Hospital, Harvard Medical School, Boston, MA, USA 4. Institute of Mechanics and Advanced Materials, Cardiff School of Engineering, Cardiff University, Wales, UK
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Abstract: | In this paper we evaluate the accuracy of warping of neuro-images using brain deformation predicted by means of a patient-specific biomechanical model against registration using a BSpline-based free form deformation algorithm. Unlike the BSpline algorithm, biomechanics-based registration does not require an intra-operative MR image which is very expensive and cumbersome to acquire. Only sparse intra-operative data on the brain surface is sufficient to compute deformation for the whole brain. In this contribution the deformation fields obtained from both methods are qualitatively compared and overlaps of Canny edges extracted from the images are examined. We define an edge based Hausdorff distance metric to quantitatively evaluate the accuracy of registration for these two algorithms. The qualitative and quantitative evaluations indicate that our biomechanics-based registration algorithm, despite using much less input data, has at least as high registration accuracy as that of the BSpline algorithm. |
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