TY - JOUR
T1 - Biomechanical model as a registration tool for image-guided neurosurgery: Evaluation against bspline registration
AU - Mostayed, Ahmed
AU - Garlapati, Revanth
AU - Joldes, Grand
AU - Wittek, Adam
AU - Roy, Aditi
AU - Kikinìs, R.M.D.
AU - Warfield, S.K.
AU - Miller, Karol
PY - 2013/11
Y1 - 2013/11
N2 - 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. © 2013 Biomedical Engineering Society.
AB - 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. © 2013 Biomedical Engineering Society.
U2 - 10.1007/s10439-013-0838-y
DO - 10.1007/s10439-013-0838-y
M3 - Article
SN - 0090-6964
VL - 41
SP - 2409
EP - 2425
JO - Annals of Biomedical Engineering
JF - Annals of Biomedical Engineering
IS - 11
ER -