Abstract
A fast fully automatic method of segmenting the prostate from 3D MR scans is presented, incorporating dynamic multi-atlas label fusion. The diffeomorphic demons method is used for non-rigid registration and a comparison of alternate metrics for atlas selection is presented. A comparison of results from an average shape atlas and the multi-atlas approach is provided. Using the same clinical dataset and manual contours from 50 clinical scans as Klein et al. (2008) a median Dice similarity coefficient of 0.86 was achieved with an average surface error of 2.00mm using the multi-atlas segmentation method.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Karlsson, M., Karlsson, M.G., Nyholm, T., Amies, C., Zackrisson, B.: Dedicated magnetic resonance imaging in the radiotherapy clinic. Int. J. Radiat. Oncol. Biol. Phys. 74, 644–651 (2009)
Raaymakers, B.W., Lagendijk, J.J.W., Overweg, J., Kok, J.G.M., Raaijmakers, A.J.E., Kerkhof, E.M., van der Put, R.W., Meijsing, I., Crijns, S.P.M., Benedosso, F., van Vulpen, M., de Graaff, C.H.W., Allen, J., Brown, K.J.: Integrating a 1.5 T MRI scanner with a 6 MV accelerator: proof of concept. Phys. Med. Biol. 54, N229–N237, (2009)
Prabhakar, R., Julka, P.K., Ganesh, T., Munshi, A., Joshi, R.C., Rath, G.K.: Feasibility of using MRI alone for 3D Radiation Treatment Planning in Brain Tumors. Japanese Journal of Clinical Oncology 37, 405–411 (2007)
Roach, M., Faillace-Akazawa, P., Malfatti, C., Holland, J., Hricak, H.: Prostate volumes defined by magnetic resonance imaging and computerized tomographic scans for three-dimensional conformal radiotherapy. Int. J. Radiat. Oncol. Biol. Phys. 35, 1011–1018 (1996)
Rasch, C., Barillot, I., Remeijer, P., Touw, A., Herk, M., van Lebesque, J.V.: Definition of the prostate in CT and MRI: a multi-observer study. International Journal of Radiation Oncology Biology Physics 43, 57–66 (1999)
Rohlfing, T., Brandt, R., Menzel, R., Maurer, C.R.: Evaluation of atlas selection strategies for atlas-based image segmentation with application to confocal microscopy images of bee brains. Neuroimage 21, 1428–1442 (2004)
Martin, S., Troccaz, J., Daanenc, V.: Automated segmentation of the prostate in 3D MR images using a probabilistic atlas and a spatially constrained deformable model. Med. Phys. 37, 1579–1590 (2010)
Klein, S., Heide, U.A., van der Lips, I.M., Vulpen, M., van Staring, M., Pluim, J.P.W.: Automatic segmentation of the prostate in 3D MR images by atlas matching using localized mutual information. Medical Physics 35, 1407–1417 (2008)
Rueckert, D., Sonoda, L.I., Hayes, C., Hill, D.L., Leach, M.O., Hawkes, D.J.: Nonrigid registration using free-form deformations: application to breast MR images. IEEE Transactions on Medical Imaging 18, 712–721 (1999)
Dowling, J., Lambert, J., Parker, J., Greer, P.B., Fripp, J., Denham, J., Ourselin, S., Salvado, O.: Automatic MRI atlas-based external beam radiation therapy treatment planning for prostate cancer. In: Madabhushi, A., et al. (eds.) MICCAI 2010. LNCS, vol. 6369, pp. 25–33. Springer, Heidelberg (2010)
Greer, P.B., Dowling, J.A., Lambert, J.A., Fripp, J., Parker, J., Denham, J.W., Wratten, C., Capp, A., Salvado, O.: A magnetic resonance imaging-based workflow for planning radiation therapy for prostate cancer. The Medical Journal of Australia 194, S24–S27 (2011)
Lambert, J., Greer, P.B., Menk, F., Patterson, J., Parker, J., Capp, A., Wratten, C., Dowling, J., Salvado, O., Hughes, C., Fisher, K., Ostwald, P., Denham, J.W.: MRI-guided prostate radiation therapy planning: Investigation of dosimetric accuracy of MRI-based dose planning. Radiotherapy and Oncology 98, 330–334 (2011)
Warfield, S.K., Zou, K.H., Wells, W.M.: Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation. IEEE Transactions on Medical Imaging 23, 903–921 (2004)
Tustison, N.J., Avants, B.B., Cook, P.A., Zheng, Y., Egan, A., Yushkevich, P.A., Gee, J.C.: N4ITK: Improved N3 Bias Correction. IEEE Transactions on Medical Imaging 29, 1310–1320 (2010)
Vercauteren, T., Pennec, X., Perchant, A., Ayache, N.: Non-parametric Diffeomorphic Image Registration with the Demons Algorithm. In: Ayache, N., Ourselin, S., Maeder, A. (eds.) MICCAI 2007, Part II. LNCS, vol. 4792, pp. 319–326. Springer, Heidelberg (2007)
Dice, L.R.: Measures of the Amount of Ecologic Association Between Species. Ecology 26, 297–302 (1945)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dowling, J.A. et al. (2011). Fast Automatic Multi-atlas Segmentation of the Prostate from 3D MR Images. In: Madabhushi, A., Dowling, J., Huisman, H., Barratt, D. (eds) Prostate Cancer Imaging. Image Analysis and Image-Guided Interventions. Prostate Cancer Imaging 2011. Lecture Notes in Computer Science, vol 6963. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23944-1_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-23944-1_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23943-4
Online ISBN: 978-3-642-23944-1
eBook Packages: Computer ScienceComputer Science (R0)