Abstract
A new method for the geometrical averaging of labels or landmarks is presented. This method expands the shape-based averaging [1] framework from an Euclidean to a geodesic based distance, incorporating a spatially varying similarity term as time cost. This framework has unique geometrical properties, making it ideal for propagating very small structures following rigorous labelling protocols. The method is used to automate the seeding and way-pointing of optic radiation tractography in DTI imaging. The propagated seeds and waypoints follow a strict clinical protocol by being geometrically constrained to one single slice and by guaranteeing spatial contiguity. The proposed method not only reduces the fragmentation of the propagated areas but also significantly increases the seed positioning accuracy and subsequent tractography results when compared to state-of-the-art label fusion techniques.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Rohlfing, T., Maurer, C.R.: Shape-based averaging. IEEE TIP 16(1), 153–161 (2007)
Parker, G.J.M., Haroon, H.A., Wheeler-Kingshott, C.A.M.: A framework for a streamline-based probabilistic index of connectivity (PICo) using a structural interpretation of MRI diffusion measurements. J. Magn. Reson. Imaging 18(2) (2003)
Bammer, R., Acar, B., Moseley, M.E.: In vivo MR tractography using diffusion imaging. European Journal of Radiology 45(3), 223–234 (2003)
Parker, G.J.M., Alexander, D.C.: Probabilistic Monte Carlo Based Mapping of Cerebral Connections Utilising Whole-Brain Crossing Fibre Information. In: Taylor, C.J., Noble, J.A. (eds.) IPMI 2003. LNCS, vol. 2732, pp. 684–695. Springer, Heidelberg (2003)
Goldberg-Zimring, D., Mewes, A.U.J., Warfield, S.K.: Diffusion Tensor Magnetic Resonance Imaging in Multiple Sclerosis. Neuroimaging (2005)
Zhang, W., Olivi, A., Hertig, S.J., van Zijl, P., Mori, S.: Automated fiber tracking of human brain white matter using diffusion imaging. NeuroImage 42(2) (2008)
Suarez, R.O., Commowick, O., Prabhu, S.P., Warfield, S.K.: Automated delineation of white matter fiber tracts with a multiple region-of-interest approach. NeuroImage 59(4), 3690–3700 (2012)
Sethian, J.A.: A fast marching level set method for monotonically advancing fronts. PNAS 93(4), 1591–1595 (1996)
Ourselin, S., Roche, A., Prima, S., Ayache, N.: Block Matching: A General Framework to Improve Robustness of Rigid Registration of Medical Images (2000)
Yogarajah, M., Focke, N.K., Bonelli, S., Cercignani, M., Acheson, J., Parker, G.J.M., Alexander, D.C., McEvoy, A.W., Symms, M.R., Koepp, M.J., Duncan, J.S.: Defining Meyer’s loop-temporal lobe resections, visual field deficits and diffusion tensor tractography. Brain 132(6), 1656–1668 (2009)
Modat, M., Ridgway, G.R., Taylor, Z.A., Lehmann, M., Barnes, J., Hawkes, D.J., Fox, N.C., Ourselin, S.: Fast free-form deformation using graphics processing units. CMPB 98(3), 278–284 (2010)
Daga, P., Winston, G., Modat, M., White, M., Mancini, L., Cardoso, M., Symms, M., Hawkes, D., Duncan, J., Ourselin, S.: Accurate Localisation of Optic Radiation during Neurosurgery in an Interventional MRI Suite. IEEE TMI (December 2011)
Alexander, D.C., Barker, G.J., Arridge, S.R.: Detection and modeling of non-Gaussian apparent diffusion coefficient profiles in human brain data. Magn. Reson. Med. 48(2), 331–340 (2002)
Crum, W.R., Camara, O., Hill, D.L.G.: Generalized Overlap Measures for Evaluation and Validation in Medical Image Analysis. IEEE TMI 25(11) (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cardoso, M.J., Winston, G., Modat, M., Keihaninejad, S., Duncan, J., Ourselin, S. (2012). Geodesic Shape-Based Averaging. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012. MICCAI 2012. Lecture Notes in Computer Science, vol 7512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33454-2_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-33454-2_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33453-5
Online ISBN: 978-3-642-33454-2
eBook Packages: Computer ScienceComputer Science (R0)