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Advances in Artificial Neural Systems
Volume 2012 (2012), Article ID 808602, 10 pages
Evaluation of a Nonrigid Motion Compensation Technique Based on Spatiotemporal Features for Small Lesion Detection in Breast MRI
1Department of Computer Science, Technical University of Munich, 85748 Garching, Germany
2Department of Scientific Computing, Florida State University, Tallahassee, FL 32306, USA
3Institute for Clinical Radiology, University of Munich, 81679 Munich, Germany
Received 17 March 2012; Accepted 21 May 2012
Academic Editor: Olivier Bastien
Copyright © 2012 F. Steinbruecker et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- S. G. Orel, M. D. Schnall, C. M. Powell et al., “Staging of suspected breast cancer: effect of MR imaging and MR-guided biopsy,” Radiology, vol. 196, no. 1, pp. 115–122, 1995.
- B. Szabó, P. Aspelin, M. Wiberg, and B. Bone, “Dynamic mr imaging of the breast—analysis of kinetic and morphologic diagnsotic criteria,” Acta Radiologica, vol. 44, no. 4, pp. 379–386, 2003.
- A. P. Schouten van der Velden, C. Boetes, P. Bult, and T. Wobbes, “Variability in the description of morphologic and contrast enhancement characteristics of breast lesions on magnetic resonance imaging,” The American Journal of Surgery, vol. 192, no. 2, pp. 172–178, 2006.
- G. M. Grimsby, R. Gray, A. Dueck et al., “Is there concordance of invasive breast cancer pathologic tumor size with magnetic resonance imaging?” The American Journal of Surgery, vol. 198, no. 4, pp. 500–504, 2009.
- S. Behrens, H. Laue, T. Boehler, B. Kuemmerlen, H. Hahn, and H. O. Peitgen, “Computer assistance for MR based diagnosis of breast cancer: present and future challenges,” Computerized Medical Imaging and Graphics, vol. 31, no. 4-5, pp. 236–247, 2007.
- A. Hill, A. Mehnert, S. Crozier, and K. McMahon, “Evaluating the accuracy and impact of registration in dynamic contrast-enhanced breast MRI,” Concepts in Magnetic Resonance B, vol. 35, no. 2, pp. 106–120, 2009.
- W. R. Crum, C. Tanner, and D. J. Hawkes, “Anisotropic multi-scale fluid registration: evaluation in magnetic resonance breast imaging,” Physics in Medicine and Biology, vol. 50, no. 21, pp. 5153–5174, 2005.
- T. Rohlfing, C. R. Maurer, D. A. Bluemke, and M. A. Jacobs, “Volume-preserving nonrigid registration of MR breast images using free-form deformation with an incompressibility constraint,” IEEE Transactions on Medical Imaging, vol. 22, no. 6, pp. 730–741, 2003.
- D. Rueckert, L. Sonoda, C. Hayes, D. Hill, M. Leach, and D. Hawkes, “Nonrigid registration using free-form deformations: application to breast mr images,” IEEE Transactions on Medical Imaging, vol. 18, no. 8, pp. 712–721, 1999.
- R. Lucht, S. Delorme, J. Heiss et al., “Classification of signal-time curves obtained by dynamic magnetic resonance mammography: statistical comparison of quantitative methods,” Investigative Radiology, vol. 40, no. 7, pp. 442–447, 2005.
- M. Y. Chu, H. M. Chen, C. Y. Hsieh et al., “Adaptive grid generation based non-rigid image registration using mutual information for breast MRI,” Journal of Signal Processing Systems, vol. 54, no. 1–3, pp. 45–63, 2009.
- B. K. P. Horn and B. G. Schunck, “Determining optical flow,” Artificial Intelligence, vol. 17, no. 1–3, pp. 185–203, 1981.
- K. H. Herrmann, S. Wurdinger, D. R. Fischer et al., “Application and assessment of a robust elastic motion correction algorithm to dynamic MRI,” European Radiology, vol. 17, no. 1, pp. 259–264, 2007.
- N. Papenberg, A. Bruhn, T. Brox, S. Didas, and J. Weickert, “Highly accurate optic flow computation with theoretically justified warping,” International Journal of Computer Vision, vol. 67, no. 2, pp. 141–158, 2006.
- S. Theodoridis and K. Koutroumbas, Pattern Recognition, Academic Press, 1998.
- D. Xu and H. Li, “Geometric moment invariants,” Pattern Recognition, vol. 41, no. 1, pp. 240–249, 2008.
- F. Jamitzky, R. W. Stark, W. Bunk et al., “Scaling-index method as an image processing tool in scanning-probe microscopy,” Ultramicroscopy, vol. 86, no. 1-2, pp. 241–246, 2001.
- W. A. Kaiser, Signs in MR Mammography, Springer, 2008.
- A. Penn, S. Thompson, C. Lehman et al., “Morphologic blooming in breast mri as a characterization of margin for discriminating benign from malignant lesions,” Academic Radiology, vol. 13, no. 11, pp. 1344–1354, 2006.
- U. Schwarz-Boeger, M. Mueller, G. Schimpfle, et al., “Moco—comparison of two different algorithms for motion correction in breast mri,” Onkologie, vol. 31, no. 2, pp. 141–158, 2008.