Nuclear Medicine & Radiation Therapy

Assessment of Similarity Measures for Accurate Deformable Image Registration

Abstract

Yuji Yaegashi, Kunihiko Tateoka, Kazunori Fujimoto, Takuya Nakazawa, Yuichi Saito, Tadanori Abe, Masaki Yano and Koichi Sakata

Purpose: Deformable image registration is widely used in radiation therapy applications. There are several different algorithms for deformable image registration. The purpose of this study was to evaluate the optimal similarity measures needed to obtain accurate deformable image registration by using a phantom.

Methods: To evaluate the optimal similarity measures for the deformable image registration, we compared several similarity measures, including the normalized correlation coefficient, the mutual information, the dice similarity coefficient, and the Tanimoto coefficient. In this study, the mutual information was normalized to have a value of 1 when there is complete correspondence between the images in order to compare it with other similarity measures. First, a reference image was acquired with the phantom located in the center of the field of view of a computed tomography. The phantom consisted of two sections a Teflon sphere and four samples of various electron density values. Then, to acquire the moving images, the phantom was scanned for various displacement values as it was moved to the left (range: 1.00-30.0 mm). Second, images for various Teflon sphere diameters (range: 0–25.4 mm) were acquired with the CT scanner. The image similarity for each condition was compared with the reference image by using several similarity measures.

Results: In the moved phantom study, although the normalized correlation coefficient, dice similarity coefficient, and Tanimoto coefficient showed the same tendency of sensitivity for measuring image similarity, the mutual information showed significant sensitivity for both of the two distinct sections of the phantom. In the study in which the phantom sphere diameter was varied, the mutual information also showed the best performance among the tested similarity measures.

Conclusions: Mutual information appears to have an advantage over other similarity measures for accurate deformable image registration.