We applied Demons and accelerated Demons elastic registration algorithm in radiotherapy cone beam CT (CBCT) images, We provided software support for real-time understanding of organ changes during radiotherapy. We wrote a 3D CBCT image elastic registration program using Matlab software, and we tested and verified the images of two patients with cervical cancer 3D CBCT images for elastic registration, based on the classic Demons algorithm, minimum mean square error (MSE) decreased 59.7%, correlation coefficient (CC) increased 11.0%. While for the accelerated demons algorithm, MSE decreased 40.1%, CC increased 7.2%. The experimental verification with two methods of demons algorithm obtained the desired results, but the small difference appeared to be lack of precision, and the total registration time was a little long. All these problems need to be further improved for accuracy and reducing of time.
Citation:
PANGHaowen, SUNXiaoyang. Application of Elastic Registration Based on Demons Algorithm in Cone Beam CT. Journal of Biomedical Engineering, 2014, 31(1): 103-106. doi: 10.7507/1001-5515.20140020
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CASTADOT P, LEE J A, PARRAGA A, et al. Comparison of 12 deformable registration strategies in adaptive radiation therapy for the treatment of head and neck tumors[J]. Radiother Oncol, 2008, 89(1):1-12.
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YAN D, JAFFRAY D A, Wong JW, et al. A model to accumulate fractionated dose in a deforming organ[J]. Int J Radiat Oncol Biol Phys, 1999, 44(3):665-675.
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THIRION J P. Image matching as a diffusion process:an analogy with Maxwell's demons[J].Med Image Anal,1998,2, 1998, 2(3):243-260.
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WANG H, DONG L, O' DANIEL J, et al. Validation of an accelerated ‘demons’ algorithm for deformable image registration in radiation therapy[J]. Phys Med Biol, 2005, 50(12):2887-2905.
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CACHIER P, PENNEC X, AYACHE N, et al. Fast non-rigid matching by gradient descent:study and improvement of the ‘Demons’ algorithm [R]. Research Report 3706, INRIA, 1999.
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- 1. MACKIE T R, KAPATOES J, RUCHALA K, et al. Image guidance for precise conformal radiotherapy[J]. Int J Radiat Oncol Biol Phys, 2003, 56(1):89-105.
- 2. NOEL C E, SANTANAM L, OLSEN J R, et al. An automated method for adaptive radiation therapy for prostate cancer patients using continuous fiducial-based tracking[J]. Phys Med Biol, 2010, 55:65-82.
- 3. YANG D, CHAUDHARI S R, GODDU S M, et al. Deformation registration of abdominal kilovoltage treatment planning CT and tomotherapy megavoltage CT for treatment adaptation[J]. Med Phys, 2009, 36(2):329-338.
- 4. CASTADOT P, LEE J A, PARRAGA A, et al. Comparison of 12 deformable registration strategies in adaptive radiation therapy for the treatment of head and neck tumors[J]. Radiother Oncol, 2008, 89(1):1-12.
- 5. YAN D, JAFFRAY D A, Wong JW, et al. A model to accumulate fractionated dose in a deforming organ[J]. Int J Radiat Oncol Biol Phys, 1999, 44(3):665-675.
- 6. THIRION J P. Image matching as a diffusion process:an analogy with Maxwell's demons[J].Med Image Anal,1998,2, 1998, 2(3):243-260.
- 7. WANG H, DONG L, O' DANIEL J, et al. Validation of an accelerated ‘demons’ algorithm for deformable image registration in radiation therapy[J]. Phys Med Biol, 2005, 50(12):2887-2905.
- 8. CACHIER P, PENNEC X, AYACHE N, et al. Fast non-rigid matching by gradient descent:study and improvement of the ‘Demons’ algorithm [R]. Research Report 3706, INRIA, 1999.