Abstract
The ordinary sample correlation coefficient is a popular similarity measure for aligning images from the same or similar modalities. However, this measure can be sensitive to the presence of "outlier" objects that appear in one image but not the other, such as surgical instruments, the patient table, etc., which can lead to biased registrations. This paper describes an intensity-based image registration technique that uses a robust correlation coefficient as a similarity measure. Relative to the ordinary sample correlation coefficient, the proposed similarity measure reduces the influence of outliers. We also compared the performance of the proposed method with the mutual information-based method. The robust correlation-based method should be useful for image registration in radiotherapy (KeV to MeV X-ray images) and image-guided surgery applications. We have investigated the properties of the proposed method by theoretical analysis, computer simulations, a phantom experiment, and with functional magnetic resonance imaging data.
| Original language | English |
|---|---|
| Pages (from-to) | 1430-1444 |
| Number of pages | 15 |
| Journal | IEEE Transactions on Medical Imaging |
| Volume | 23 |
| Issue number | 11 |
| DOIs | |
| State | Published - Nov 2004 |
Bibliographical note
Funding Information:Manuscript received July 2, 2003; revised January 30, 2004. This work was supported in part by the National Institutes of Health (NIH) under Grant P01-CA59827, Grant R01-CA81161, and Grant R01-CA60711. The Associate Editor responsible for coordinating the review of this paper and recommending its publication was M. H. Lowe. Asterisk indicates corresponding author. *J. Kim is with the Information Electronics Department, Ewha Womans University, Seoul 120-750, Korea (e-mail: [email protected]).
Keywords
- Image registration
- Mutual information
- Outlier
- Robust correlation coefficient
- Robustness