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Mutual information-based CT-MR brain image registration using generalized partial volume joint histogram estimation.
IEEE Trans Med Imaging. 2003 Sep; 22(9):1111-9.IT

Abstract

Mutual information (MI)-based image registration has been found to be quite effective in many medical imaging applications. To determine the MI between two images, the joint histogram of the two images is required. In the literature, linear interpolation and partial volume interpolation (PVI) are often used while estimating the joint histogram for registration purposes. It has been shown that joint histogram estimation through these two interpolation methods may introduce artifacts in the MI registration function that hamper the optimization process and influence the registration accuracy. In this paper, we present a new joint histogram estimation scheme called generalized partial volume estimation (GPVE). It turns out that the PVI method is a special case of the GPVE procedure. We have implemented our algorithm on the clinically obtained brain computed tomography and magnetic resonance image data furnished by Vanderbilt University. Our experimental results show that, by properly choosing the kernel functions, the GPVE algorithm significantly reduces the interpolation-induced artifacts and, in cases that the artifacts clearly affect registration accuracy, the registration accuracy is improved.

Authors+Show Affiliations

Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA. hchen@cse.uta.eduNo affiliation info available

Pub Type(s)

Comparative Study
Evaluation Study
Journal Article
Research Support, U.S. Gov't, Non-P.H.S.
Research Support, U.S. Gov't, P.H.S.
Validation Study

Language

eng

PubMed ID

12956266

Citation

Chen, Hua-Mei, and Pramod K. Varshney. "Mutual Information-based CT-MR Brain Image Registration Using Generalized Partial Volume Joint Histogram Estimation." IEEE Transactions On Medical Imaging, vol. 22, no. 9, 2003, pp. 1111-9.
Chen HM, Varshney PK. Mutual information-based CT-MR brain image registration using generalized partial volume joint histogram estimation. IEEE Trans Med Imaging. 2003;22(9):1111-9.
Chen, H. M., & Varshney, P. K. (2003). Mutual information-based CT-MR brain image registration using generalized partial volume joint histogram estimation. IEEE Transactions On Medical Imaging, 22(9), 1111-9.
Chen HM, Varshney PK. Mutual Information-based CT-MR Brain Image Registration Using Generalized Partial Volume Joint Histogram Estimation. IEEE Trans Med Imaging. 2003;22(9):1111-9. PubMed PMID: 12956266.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Mutual information-based CT-MR brain image registration using generalized partial volume joint histogram estimation. AU - Chen,Hua-Mei, AU - Varshney,Pramod K, PY - 2003/9/6/pubmed PY - 2004/1/30/medline PY - 2003/9/6/entrez SP - 1111 EP - 9 JF - IEEE transactions on medical imaging JO - IEEE Trans Med Imaging VL - 22 IS - 9 N2 - Mutual information (MI)-based image registration has been found to be quite effective in many medical imaging applications. To determine the MI between two images, the joint histogram of the two images is required. In the literature, linear interpolation and partial volume interpolation (PVI) are often used while estimating the joint histogram for registration purposes. It has been shown that joint histogram estimation through these two interpolation methods may introduce artifacts in the MI registration function that hamper the optimization process and influence the registration accuracy. In this paper, we present a new joint histogram estimation scheme called generalized partial volume estimation (GPVE). It turns out that the PVI method is a special case of the GPVE procedure. We have implemented our algorithm on the clinically obtained brain computed tomography and magnetic resonance image data furnished by Vanderbilt University. Our experimental results show that, by properly choosing the kernel functions, the GPVE algorithm significantly reduces the interpolation-induced artifacts and, in cases that the artifacts clearly affect registration accuracy, the registration accuracy is improved. SN - 0278-0062 UR - https://www.unboundmedicine.com/medline/citation/12956266/Mutual_information_based_CT_MR_brain_image_registration_using_generalized_partial_volume_joint_histogram_estimation_ DB - PRIME DP - Unbound Medicine ER -