Estimation of Surface-Based Target Registration Error Under Heteroscedastic Noise

Project Supervisor: Burton Ma


Objective
 The goal of the project is to derive an analytic expression for target registration error (TRE) for shape based registration under heteroscedastic measurement noise, and to validate the expression using simulated registration data. Real world data will be collected and used during the validation process if time permits.


Project References
 [1] B. Ma, M. H. Moghari, R. E. Ellis, and P. Abolmaesumi. “Estimation of optimal fiducial target registration error in the presence of heteroscedastic noise”. IEEE Transactions on Medical Imaging, vol. 29, no. 3, pp. 708-723, 2010.

[2] R. Sandhu, S. Dambreville, and A. Tannenbaum. “Point set registration via particle filtering and stochastic dynamics”. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 32, no. 8, pp. 1459-1473, 2010.

[3] P. J. Besl and N. D. McKay. “A method for registration of 3-D shapes”. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 2, pp. 239-255, 1992.

[4] B. Ma and R. E. Ellis, “Analytic expressions for fiducial and surface target registration error,” in Medical Image Computing and Computer Assisted Intervention, ser. Lecture Notes in Computer Science, R. Larsen, M. Nielsen, and J. Sporring, Eds. Springer Berlin / Heidelberg, 2006, vol. 4191, pp. 637–644.

[5] J. M. Fitzpatrick, J. B. West, and C. R. Maurer, Jr. “Predicting error in rigid-body point-based registration”. IEEE Transactions on Medical Imaging, vol. 17, no. 5, pp. 694-702, 1998.

[6] L. Walia. CSE4080 report, 2010.

[7] K. Schindler and H. Bischof. “On robust regression in photogrammetric point clouds”. Lecture notes on computer science, vol. 2781, pp 172-178, 2003.

[8] B. Matei and P. Meer. “Optimal rigid motion estimation and performance evaluation with bootstrap,” in IEEE Conference on Computer Vision and Pattern Recognition, IEEE Computer Society, 1999, pp. 1339-1345.

[9] R. S. J. Estpar, A. Brun, and C.-F. Westin, “Robust generalized total least squares iterative closest point registration,” in Medical Image Computing and Computer Assisted Intervention, ser. Lecture Notes in Computer Science, C. Barillot, D. R. Haynor, and P. Hellier, Eds. Springer Berlin / Heidelberg, 2004, vol.3216, pp. 234–241.

[10] R. M. Murray, Z. Li, and S. S. Sastry. “Rigid body motion” in A Mathematical Introduction to Robotic Manipulation, 2nd ed., CRC Press, 1994, pp. 19-51.


Last updated: October 27, 2010