Biomechanical model as a registration tool for image-guided neurosurgery: Evaluation against bspline registration

Ahmed Mostayed, Revanth Garlapati, Grand Joldes, Adam Wittek, Aditi Roy, R.M.D. Kikinìs, S.K. Warfield, Karol Miller

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)

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. © 2013 Biomedical Engineering Society.
Original languageEnglish
Pages (from-to)2409-2425
JournalAnnals of Biomedical Engineering
Volume41
Issue number11
Early online date15 Jun 2013
DOIs
Publication statusPublished - Nov 2013

Fingerprint

Dive into the research topics of 'Biomechanical model as a registration tool for image-guided neurosurgery: Evaluation against bspline registration'. Together they form a unique fingerprint.

Cite this