Xiaofen Zheng, Jayaram Udupa, Xinjian Chen Medical Image
Processing Group Department of Radiology University of Pennsylvania
Feb 10, 2008 (4:30 4:50pm) Cluster of Workstation Based Non-rigid
Image Registration Using Free-Form Deformation
Slide 2
Outline 3D nonrigid registration method and its parallelization
Large image data sets Parallel computing: cluster of workstations
(COW) Results Time analysis: sequential vs. parallel
Registration Algorithm B-spline coefficients Image pyramid
Optimization Output computing B-spline image representation and
coefficients using 1-D recursive filters [Unser1991] Thevenaz and
Unsers image model via cubic Bspline [Thvenaz 2000]
Slide 7
Registration Algorithm B-spline coefficients Image pyramid
Optimization Output computing Analytic method of computing gradient
of MI [Thvenaz 2000] Stochastic gradient descent optimization
[Klein 2007]
Slide 8
Optimization Derivative of Mutual Information (MI) [Thvenaz
2000]
Slide 9
Slide 10
Registration Algorithm B-spline coefficients Image pyramid
Optimization Output computing Control points refinement between two
levels [Maurer 2000]
Slide 11
Registration Algorithm B-spline coefficients Image pyramid
Optimization Output computing Cubic B-spline Deformation [Mattes
2003] Thevenaz and Unsers image model via cubic Bspline [Thvenaz
2000]
Slide 12
Experiment 10 workstations (each has Pentium D 3.4 GHz CPU and
4 GB of main memory) through 1GB/s switch Large CT image Size :
512512459, voxel: 0.680.681.5 mm^3 Control mesh: 272752 (113,724)
100 iteration of optimization in each level Regular brain MRI image
Size : 25625646, voxel: 0.980.983 mm^3 Control mesh: 272715
(10,935) 100 iteration of optimization in each level
Slide 13
Time analysis (sequential vs. parallel) Scaled time comparison
for sequential and parallel computing for each step on each
level.
Slide 14
Cumulative Time cost of sequential, parallel and combined
solution in each step.
Slide 15
Results (large image) Reference image (original CT image)Test
image (known deformed image)Overlay test image with reference
imageOutput imageOverlay output image with reference image
Slide 16
Results (large image) Reference image (original CT image)Test
image (known deformed image)Overlay test image with reference
imageOutput imageOverlay output image with reference image
Slide 17
Results (regular image) Reference image (original brain MRI
image)Test image (deformed image)Overlay reference image with test
imageOutput imageOverlay reference image with output image
Slide 18
Conclusion Important to tackle time-critical clinical
applications A general parallel strategy Complex interplay
Implemented in CAVASS software
Slide 19
Reference [Klein 2007] Stefan Klein, Marius Staring, Josien
P.W. Pluim, Evaluation of Optimization Methods for Nonrigid Medical
Image Registration using Mutual Information and B-splines, IEEE
Transactions on Image Processing, vol. 16, pp. 2879-2890, 2007.
[Thvenaz 2000] Philippe Thvenaz, Michael Unser, Optimization of
Mutual Information for Multiresolution Image Registration, IEEE
Transactions on Image Processing, vol. 9, no. 12, pp. 2083-2099,
December 2000. [Unser1993] Michael Unser, Akram Aldroubi, Murray
Eden, The L2 Polynomial Spline Pyramid, IEEE Transactions on
Pattern Analysis and Machine Intelligence, vol. 15, no. 4, pp.
364-379, April 1993 [Unser1991] Michael Unser, Akram Aldroubi,
Murray Eden, Fast B-Spline Transforms for Continuous Image
Representation and Interpolation, IEEE Transactions on Pattern
Analysis and Machine Intelligence, vol. 13, no. 3, pp. 277-285,
March 1991. [Maurer2003] Torsten Rohlfing, Calvin R. Maurer,
Nonrigid Image Registration in Shared-Memory Multiprocessor
Environments with Application to Brains, Breasts, and Bees, IEEE
Transactions on Information Technology in Biomedicine, vol. 7, no.
1, pp. 16-25, March 2003. [Rohlfing2001] Torsten Rohlfing, Calvin
R. Maurer, Walter G. ODell, Jianhui Zhong, Modeling liver motion
and deformation during the respiratory cycle using intensity-based
free-form registration of gated MR images, SPIE Medical Imaging
Conference Proceedings vol. 4319, pp. 337-348, 2001. [Mattes 2003]
Mattes, D., Haynor, D. R., Vesselle, H., Lewellen, T. K., and
Eubank, W., PET-CT image registration in the chest using free-form
deformations, IEEE Transactions on Medical Imaging 22(1), pp.120
128, 2003. [Maurer 2001] Rohlfing, T., Maurer, C. R., ODell, W. G.,
and Zhong, J., Modeling liver motion and deformation during the
respiratory cycle using intensity-based free-form registration of
gated MR images, Medical Imaging, Proc. SPIE 4319, pp. 337348,
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