Abstract
Validation of computer-aided detection and intervention procedures for prostate cancer is still a challenging issue. Despite the increasing accuracy of prostate image analysis tools, in vivo and in silico validations are necessary before they can be deployed in clinical routine. In this study, we developed a statistical atlas of prostate morphology for construction of realistic digital and physical phantoms. We have been interested in modeling the gland’s zonal anatomy as defined by the peripheral zone and the central gland. Magnetic Resonance Imaging studies from 30 patients were used. Mean shape and most relevant deformations for prostate structures were computed using principal component analysis. The resulting statistical atlas has been used in image simulation and the design of a physical phantom of the prostate.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Collins, D.L., Zijdenbos, A.P., kollokian, V., Sled, J.G., Kabani, N.J., Holmes, C.J., Evans, A.C.: Design and construction of a realistic digital brain phantom. IEEE Trans. Med. Img. 17(3), 463–468 (1998)
Shen, D., Lao, Z., Zeng, J., Zhang, W., Sesterhenn, I.A., Sun, L., Moul, J.W., Herskovits, E.H., Fichtinger, G., Davatzikos, C.: Optimized prostate biopsy via statistical atlas of cancer spatial distribution. Medical Image Analysis 8, 139–150 (2004)
McNeal, J.E.: The zonal anatomy of the prostate. Prostate 2, 35–49 (1981)
Villers, A., Grosclaude, P.: Epidemiology of prostate cancer. Médecine Nucléaire 32(1), 2–4 (2007)
Bushman, W.: Etiology, epidemiology, and natural history of benign prostatic hyperplasia. Urologic Clinics of North America 36(4), 403–415 (2009)
Bosch, J.L., Tilling, K., Bohnen, A.M., Bangma, C.H., Donovan, J.L.: Establishing normal reference ranges for prostate volume change with age in the population-based Krimpen-study: prediction of future prostate volume in individual men. Prostate 67, 1816–1824 (2007)
Subsol, G., Thirion, J.P., Ayache, N.: A scheme for automatically building three-dimensional morphometric anatomical atlases: application to a skull atlas. Medical Image Analysis 2(1), 37–60 (1998)
Pasquier, D., Lacornerie, T., Vermandel, M., Rousseau, J., Lartigau, E., Betrouni, N.: Automatic segmentation of pelvic structures from magnetic resoncance images for prostate cancer radiotherapy. International Journal of Oncology Biology Physics 68(2), 592–600 (2007)
Klein, S., Van der Heide, U.A., Lips, I.M., Van Vulpen, M., Staring, M., Pluim, J.P.: Automatic segmentation of the prostate in 3D MR images by atlas matching using localized mutual information. Med. Phys. 35(4), 1407–1417 (2008)
Makni, N., Puech, P., Lopes, R., Dewalle, A.S., Colot, O., Betrouni, N.: Combining a deformable model and a probabilistic framework for an automatic 3D segmentation of prostate on MRI. International Journal of Computer Assisted Radiology and Surgery 4(2), 181–188 (2009)
Toth, R., Tiwari, P., Rosen, M., Reed, G., Kurhanewicz, J., Kalyanpur, A., Pungavkar, S., Madabhushi, A.: A Magnetic Resonance Spectroscopy Driven Initialization Scheme for Active Shape Model Based Prostate Segmentation. Medical Image Analysis 15(2), 214–225 (2010)
Besl, P.J., Mckay, N.D.: A Method for Registration of 3-D Shapes. IEEE Transactions on Pattern Analysis and Matching Intelligence 14(2), 239–256 (1992)
Chui, H., Rangarajan, A.: A new algorithm for non rigid point matching. Computer Vision and Image Understanding 89(2-3), 114–141 (2003)
Bookstein, F.: Principal warps: Thin-plate splines and the decomposition of deformations. IEEE Transactions on Pattern Analysis and Matching Intelligence 11(6), 567–585 (1989)
Cootes, T.F., Hill, A., Taylor, C.J., Haslam, J.: The use of Active Shape Models For Locating Structures in Medical Images. Image Vision and Computing 12(6), 355–366 (1994)
Atalar, E., Ménard, C.: MR-guided interventions for prostate cancer. Magnetic Resonance Imaging Clinics of North America 13, 491–504 (2005); prostate carcinoma: Areview. Medical Image Analysis 10, 178–199 (2006)
Benoit-Cattin, H., Collewet, G., Belaroussi, B., Saint-Jalmes, H., Odet, C.: The SIMRI project: a versatile and interactive MRI simulator. J. Magn. Reson. 173(1), 97–115 (2005)
Lindner, U., Lawrentschuk, N., Weersink, R.A., Raz, O., Hlasny, E., Sussman, M.S., Davidson, S.R., Gertner, M.R., Trachtenberg, J.: Construction and evaluation of an anatomically correct multi-image modality compatible phantom for prostate cancer focal ablation. J. Urol. 184(1), 352–357 (2010)
Desbrun, M., Meyer, M., Schröder, P., Barr, A.H.: Implicit fairing of irregular meshes using diffusion and curvature flow. In: Proceedings of the 26th Annual Conference on Computer Graphics and Interactive Techniques, pp. 317–324 (1999)
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
Makni, N., Iancu, A., Puech, P., Mordon, S., Betrouni, N. (2011). A Morphological Atlas of Prostate’s Zonal Anatomy for Construction of Realistic Digital and Physical Phantoms. 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_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-23944-1_3
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)