Evaluation of deformable image registration and a motion model in CT images with limited features.

Abstract:

:Deformable image registration (DIR) is increasingly used in radiotherapy applications and provides the basis for a previously described model of patient-specific respiratory motion. We examine the accuracy of a DIR algorithm and a motion model with respiration-correlated CT (RCCT) images of software phantom with known displacement fields, physical deformable abdominal phantom with implanted fiducials in the liver and small liver structures in patient images. The motion model is derived from a principal component analysis that relates volumetric deformations with the motion of the diaphragm or fiducials in the RCCT. Patient data analysis compares DIR with rigid registration as ground truth: the mean ± standard deviation 3D discrepancy of liver structure centroid positions is 2.0 ± 2.2 mm. DIR discrepancy in the software phantom is 3.8 ± 2.0 mm in lung and 3.7 ± 1.8 mm in abdomen; discrepancies near the chest wall are larger than indicated by image feature matching. Marker's 3D discrepancy in the physical phantom is 3.6 ± 2.8 mm. The results indicate that visible features in the images are important for guiding the DIR algorithm. Motion model accuracy is comparable to DIR, indicating that two principal components are sufficient to describe DIR-derived deformation in these datasets.

journal_name

Phys Med Biol

authors

Liu F,Hu Y,Zhang Q,Kincaid R,Goodman KA,Mageras GS

doi

10.1088/0031-9155/57/9/2539

subject

Has Abstract

pub_date

2012-05-07 00:00:00

pages

2539-54

issue

9

eissn

0031-9155

issn

1361-6560

journal_volume

57

pub_type

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