Comparison of Similarity Measures for Rigid-body CT/Dual X-ray Image Registrations

Abstract

A set of experiments were conducted to evaluate six similarity measures for intensity-based rigid-body 3D/2D image registration. Similarity measure is an index that measures the similarity between a digitally reconstructed radiograph (DRR) and an x-ray planar image. The registration is accomplished by maximizing the sum of the similarity measures between biplane x-ray images and the corresponding DRRs in an iterative fashion. We have evaluated the accuracy and attraction ranges of the registrations using six different similarity measures on phantom experiments for head, thorax, and pelvis. The images were acquired using Varian Medial System On-Board Imager. Our results indicated that normalized cross correlation and entropy of difference showed a wide attraction range (62 deg and 83 mm mean attraction range, ω_mean), but the worst accuracy (4.2 mm maximum error, e_max). The gradient-based similarity measures, gradient correlation and gradient difference, and the pattern intensity showed sub-millimeter accuracy, but narrow attraction ranges (ω_mean=29 deg, 31 mm). Mutual information was in-between of these two groups (e_max=2.5 mm, ω_mean= 48 deg, 52 mm). On the data of 120 x-ray pairs from eight IRB approved prostate patients, the gradient difference showed the best accuracy. In the clinical applications, registrations starting with the mutual information followed by the gradient difference may provide the best accuracy and the most robustness.

Keywords

3D/2D image registration Similarity measures Patient positioning Image guided radiation therapy

References

Booth

Modeling the impact of treatment uncertainties in radiotherapy. University of Adelaide (2002).

Gall

K.P.

Verhey

L. J.

Wagner

Computer-assisted positioning of radiotherapy patients using implanted radiopaque fiducials. Medical Physics 20, 1153–1159 (1993).

Shirato

Physical aspects of a real-time tumor-tracking system for gated radiotherapy. International Journal of Radiation Oncology, Biology, Physics 48, 1187–1195 (2000).

Bijhold

Three-dimensional verification of patient placement during radiotherapy using portal images. Medical Physics 20, 347 (1993).

Gilhuijs

K. G. A.

van de Ven

P. J. H.

van Herk

Automatic three-dimensional inspection of patient setup in radiation therapy using portal images, simulator images, and computed tomography data. Medical Physics 23, 389–399 (1996).

Uematsu

A dual computed tomography linear accelerator unit for stereotactic radiation therapy: A new approach without cranially fixated stereotactic frames. International Journal of Radiation Oncology, Biology, Physics 35, 587–592 (1996).

Murphy

M. J.

An automatic six-degree-of-freedom image registration algorithm for image-guided frameless stereotaxic radiosurgery. Medical Physics 24, 857–866 (1997).

Berbeco

R. I.

Integrated radiotherapy imaging system(IRIS): Design considerations of tumour tracking with linac gantry-mounted diagnostic x-ray systems with flat-panel detectors. Physics in Medicine and Biology 49, 243–255 (2004).

Djajaputra

Real-time 3D surface-image-guided beam setup in radiotherapy of breast cancer. Medical Physics 32, 65–75 (2005).

10.

Bova

F. J.

The University of Florida frameless high-precision stereotactic radiotherapy system. International Journal of Radiation Oncology, Biology, Physics 38, 875–882 (1997).

11.

Feldmar

Ayache

Betting

3D-2D projective registration of free-form curves and surfaces. In INRIA Report 2434. (1994).

12.

Liu

Bullitt

Pizer

S. M.

3D/2D registration via skeletal near projective invariance in tubular objects. In Medical Image Computing and Computer-Assisted Interventation — MICCAI7'98. Springer (1998).

13.

Brown

L. M. G.

Boult

T. E.

Registration of Planar Film Radiographs with Computed Tomography. In 1996 Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA '96) (1996).

14.

Weese

Voxel-based 2-D/3-D registration of fluoroscopy images and CT scansfor image-guided surgery. IEEE Transactions on Information Technology in Biomedicine 1, 284–293 (1997).

15.

Cosman

Rigid Registration of MR and Biplanar Fluoroscopy. Massachusetts Institute of Technology (2000).

16.

LaRose

D. A.

X-Ray/CT Registration Using Accelerated Volume Rendering. Carnegie Mellon University (2001).

17.

Zollei

2D-3D Rigid-Body Registration of X-Ray Fluoroscopy and CT Images. Massachusetts Institute of Technology (2001).

18.

Lacroute

Levoy

Fast volume rendering using a shear-warp factorization of the viewing transformation. In SIGGRAPH 94. ACM Press New York, NY, USA (1994).

19.

Salama

C. R.

Volume Rendering Techniques for General Purpose Graphics Hardware. Univ. Erlangen-Nürnberg (2001).

20.

Kim

Characteristics of A CT/Dual X-Ray Image Registration Method Using 2D Texturemap DRR, Gradient Ascent, and Mutual Information. In International Conference on the Use of Computers in Radiation Therapy (2004).

21.

Clippe

Patient setup error measurement using 3D intensity-based image registration techniques. International Journal of Radiation Oncology, Biology, Physics 56, 259–265 (2003).

22.

Studholme

Hill

D. L.

Hawkes

D. J.

Automated 3-D registration of MR and CT images of the head. Medical Image Analysis 1, 163–175 (1996).

23.

Studholme

Hill

D. L. G.

Hawkes

D. J.

Automated three-dimensional registration of magnetic resonance and positron emission tomography brain images by multiresolution optimization of voxel similarity measures. Medical Physics 24, 25 (1997).

24.

Bro-Nielsen

Rigid registration of CT, MR and cryosection images using a GLCM framework. In CVRMed-MRCAS. (1997).

25.

Penney

G. P.

A comparison of similarity measures for use in 2-D-3-D medicalimage registration. IEEE Transactions on Medical Imaging 17, 586–595 (1998).

26.

Holden

Voxel similarity measures for 3-D serial MR brain imageregistration. IEEE Transactions on Medical Imaging 19, 94–102 (2000).

27.

Hipwell

J. H.

Intensity-based 2-D-3-D registration of cerebral angiograms. IEEE Transactions on Medical Imaging 22, 1417–1426 (2003).

28.

Pluim

J. P. W.

Maintz

J. B. A.

Viergever

M. A.

f-information measures in medical image registration. IEEE Transactions on Medical Imaging 23, 1508–1516 (2004).

29.

Khamene

Automatic registration of portal images and volumetric CT for patient positioning in radiation therapy. Medical Image Analysis 10, 96–112 (2006).

30.

Kim

Effects of x-ray and CT image enhancements on the robustness and accuracy of a rigid 3D/2D image registration. Medical Physics 32, 866–873 (2005).

31.

Nelder

J. A.

Mead

A simplex method for function minimization. Computer Journal 7, 308–313 (1965).

32.

Viola

Alignment by Maximization of Mutual Information. In MIT Technical Report 154, MIT (1995).

33.

Kim

A feasibility study of mutual information based setup error estimation for radiotherapy. Medical Physics 28, 2507–2517 (2001).

34.

Weese

An approach to 2D/3D registration of a vertebra in 2D X-ray fluoroscopies with 3D CT images. In Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery. Springer-Verlag London, UK (1997).

35.

Birkfellner

Rigid 2D/3D slice-to-volume registration and its application on fluoroscopic CT images. Medical Physics 34, 246–255 (2007).