nach oben

Erschienen in:

2014 | OriginalPaper | Buchkapitel

Total Variation Regularization of Displacements in Parametric Image Registration

verfasst von : Valeriy Vishnevskiy, Tobias Gass, Gábor Székely, Orcun Goksel

Erschienen in: Abdominal Imaging. Computational and Clinical Applications

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Spatial regularization is indispensable in image registration to avoid both physically implausible displacement fields and potential local minima in optimization methods. Typical \(\ell _2\)-regularization is incapable of correctly recovering non-smooth displacement fields, such as at sliding organ boundaries during time-series of breathing motion. In this paper, Total Variation (TV) regularization is used to allow for accurate registration near such boundaries. We propose a novel formulation of TV-regularization for parametric displacement fields and introduce an efficient and general numerical solution scheme using the Alternating Directions Method of Multipliers (ADMM). Our method has been evaluated on two public datasets of 4D CT lung images as well as a dataset of 4D MR liver images, demonstrating accurate registrations both inside and outside moving organs. The target registration error of our method is 2.56 mm on average in the liver dataset, which indicates an improvement of over 24 % in comparison to other published methods.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel A Novel Visualization Technique for Virtual Colonoscopy Using One-Sided Transparency

Nächstes Kapitel A Bilinear Model for Temporally Coherent Respiratory Motion

http://www.di.ens.fr/~mschmidt/Software/minFunc.html.

http://www.creatis.insa-lyon.fr/rio/popi-model.

http://www.dir-lab.com.

Hu, S., Hoffman, E.A., Reinhardt, J.M.: Automatic lung segmentation for accurate quantitation of volumetric X-ray CT images. IEEE Trans. Med. Imaging 20, 490–498 (2001)CrossRef

Delmon, V., Rit, S., Pinho, R., Sarrut, D.: Registration of sliding objects using direction dependent B-splines decomposition. Phys. Med. Biol. 58, 1303–1314 (2013)CrossRef

Kiriyanthan, S., Fundana, K., Cattin, P.C.: Discontinuity preserving registration of abdominal MR images with apparent sliding organ motion. In: Yoshida, H., Sakas, G., Linguraru, M.G. (eds.) Abdominal Imaging. LNCS, vol. 7029, pp. 231–239. Springer, Heidelberg (2012)

Chan, T.F., Esedoglu, S., Nikolova, M.: Algorithms for finding global minimizers of image segmentation and denoising models. SIAM J. Appl. Math. 66, 1632–1648 (2006)CrossRefMathSciNetMATH

Castillo, E., Castillo, R., Martinez, J., Shenoy, M., Guerrero, T.: Four-dimensional deformable image registration using trajectory modeling. Phys. Med. Biol. 55, 305–327 (2010)CrossRef

Risser, L., Vialard, F.X., Baluwala, H.Y., Schnabel, J.A.: Piecewise-diffeomorphic image registration: Application to the motion estimation between 3D CT lung images with sliding conditions. Med. Image Anal. 17, 182–193 (2013)CrossRef

Papież, B.W., Heinrich, M.P., Risser, L., Schnabel, J.A.: Complex lung motion estimation via adaptive bilateral filtering of the deformation field. In: Mori, K., Sakuma, I., Sato, Y., Barillot, C., Navab, N. (eds.) MICCAI 2013, Part III. LNCS, vol. 8151, pp. 25–32. Springer, Heidelberg (2013)CrossRef

Tanner, C., Samei, G., Székely, G.: Investigating anisotropic diffusion for the registration of abdominal MR images. In: IEEE International Symposium on Biomedical Imaging (ISBI), pp. 484–7 (2013)

Sun, D., Roth, S., Black, M.J.: Secrets of optical flow estimation and their principles. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 2432–2439 (2010)

10.

Glocker, B., Komodakis, N., Tziritas, G., Navab, N., Paragios, N.: Dense image registration through MRFs and efficient linear programming. Med. Image Anal. 12, 731–741 (2008)CrossRef

11.

Heinrich, H., Jenkinson, M., Brady, M., Schnabel, J.A.: MRF-based deformable registration and ventilation estimation of lung CT. IEEE Trans. Med. Imaging 32, 1239–1248 (2013)CrossRef

12.

Pock, T., Urschler, M., Zach, C., Beichel, R.R., Bischof, H.: A duality based algorithm for TV-\(\mathit{L}^{1}\)-optical-flow image registration. In: Ayache, N., Ourselin, S., Maeder, A. (eds.) MICCAI 2007, Part II. LNCS, vol. 4792, pp. 511–518. Springer, Heidelberg (2007)CrossRef

13.

Hermann, S., Werner, R.: TV-L\(_{1}\)-based 3D medical image registration with the census cost function. In: Klette, R., Rivera, M., Satoh, S. (eds.) PSIVT 2013. LNCS, vol. 8333, pp. 149–161. Springer, Heidelberg (2014)CrossRef

14.

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 Trans. Med. Imaging 18, 712–721 (1999)CrossRef

15.

Boyd, S., Parikh, N., Chu, E., Peleato, B., Eckstein, J.: Distributed optimization and statistical learning via the alternating direction method of multipliers. Found. Trends Mach. Learn. 3, 1–122 (2011)CrossRef

16.

Figueiredo, M.A., Bioucas-Dias, J.M.: Algorithms for imaging inverse problems under sparsity regularization. In: IEEE Int Workshop on Cognitive Information Processing (CIP), pp. 1–6 (2012)

17.

Schwarz, L.A.: Non-rigid registration using free-form deformations. Ph.D. thesis, Technische Universität München, Germany (2007)

18.

Vandemeulebroucke, J., Sarrut, D., Clarysse, P., et al.: The POPI-model, a point-validated pixel-based breathing thorax model. In: International Conference on Computers in Radiation Therapy (ICCR), pp. 195–9 (2007)

Titel: Total Variation Regularization of Displacements in Parametric Image Registration
verfasst von: Valeriy Vishnevskiy
Tobias Gass
Gábor Székely
Orcun Goksel
Verlag: Springer International Publishing
Buch: Abdominal Imaging. Computational and Clinical Applications
Print ISBN: 978-3-319-13691-2

Electronic ISBN: 978-3-319-13692-9

Copyright-Jahr: 2014
DOI: https://doi.org/10.1007/978-3-319-13692-9_20

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"