Development of a Software for 3D Virtual Phantom Design_Journal of Biomedical Engineering

Authors：

 ZOULian ^1,2 , XIEZhao ^1,2 , WUQi ^1,2

1. Joint Laboratory for Medical Physics, Sichuan Provincial People's Hospital, Chengdu 610072, China;
2. Department of Oncology, Sichuan Provincial People's Hospital, Chengdu 610072, China;

Corresponding author：

ZOULian, Email: zoulian_medphy@sina.com

Keywords：

3D virtual phantom; virtual CT scanner; Monte Carlo dose simulation; image reconstruction algorithm

DOI：

10.7507/1001-5515.20140015

Video：

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In this paper, we present a 3D virtual phantom design software, which was developed based on object-oriented programming methodology and dedicated to medical physics research. This software was named Magical Phantom (MPhantom), which is composed of 3D visual builder module and virtual CT scanner. The users can conveniently construct any complex 3D phantom, and then export the phantom as DICOM 3.0 CT images. MPhantom is a user-friendly and powerful software for 3D phantom configuration, and has passed the real scene's application test. MPhantom will accelerate the Monte Carlo simulation for dose calculation in radiation therapy and X ray imaging reconstruction algorithm research.

Citation： ZOULian, XIEZhao, WUQi. Development of a Software for 3D Virtual Phantom Design. Journal of Biomedical Engineering, 2014, 31(1): 76-80. doi: 10.7507/1001-5515.20140015 Copy

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8.	SÖHN M, SOBOTTA B, ALBER M. Dosimetric treatment course simulation based on a statistical model of deformable organ motion[J]. Phys Med Biol, 2012, 57(12):3693-3709.
9.	ROLAND T, HALES R, MCNUTT T, et al. A method for deriving a 4D-interpolated balanced planning target for mobile tumor radiotherapy[J]. Med Phys, 2012, 39(1):195-205.
10.	CAON M. Voxel-based computational models of real human anatomy:a review[J]. Radiat Environ Biophys, 2004, 42(4):229-235.
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13.	Python Software Foundation. Python v 2.7.3 documentation[EB/OL](2011-06-12)[2012-05-20].http://docs.python.org/2/library/index.html.
14.	THOMAS S J. Relative electron density calibration of CT scanners for radiotherapy treatment planning[J]. Br J Radiol, 1999, 72(860):781-786.
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1. MA C M, JIANG S B, PAWLICKI T, et al. A quality assurance phantom for IMRT dose verification[J]. Phys Med Biol, 2003, 48(5):561-572.
2. YOO S, YIN F F. Dosimetric feasibility of cone-beam CT-based treatment planning compared to CT-based treatment planning[J]. Int J Radiat Oncol Biol Phys, 2006, 66(5):1553-1561.
3. OUYANG L, SOLBERG T, WANG J. Noise reduction in low-dose cone beam CT by incorporating prior volumetric image information[J]. Med Phys, 2012, 39(5):2569-2577.
4. PETER J, JASZCZAK R, COLEMAN R. Composite quadric-based object model for SPECT Monte-Carlo simulation[C]//45th Annual Meeting of the Society of Nuclear Medicine, Toronto:1998:121P.
5. PETER J, GILLAND D R, JASZCZAK R J, et al. Four-dimensional superquadric-based cardiac phantom for Monte Carlo simulation of radiological imaging systems[J]. IEEE Trans Nucl Sci, 1999, 46(6):2211-2217.
6. SEGARS W P, XCAT T B. The evolution of 4-D computerized phantoms for imaging research[J]. Proceedings of the IEEE, 2009, 97(12):1954-1968.
7. SEGARS W P, STURGEON G, MENDONCA S, et al. 4D XCAT phantom for multimodality imaging research[J]. Med Phys, 2010, 37(9):4902-4915.
8. SÖHN M, SOBOTTA B, ALBER M. Dosimetric treatment course simulation based on a statistical model of deformable organ motion[J]. Phys Med Biol, 2012, 57(12):3693-3709.
9. ROLAND T, HALES R, MCNUTT T, et al. A method for deriving a 4D-interpolated balanced planning target for mobile tumor radiotherapy[J]. Med Phys, 2012, 39(1):195-205.
10. CAON M. Voxel-based computational models of real human anatomy:a review[J]. Radiat Environ Biophys, 2004, 42(4):229-235.
11. PETER J, TORNAI M P, JASZCZEK R J. Analytical versus voxelized phantom representation for Monte Carlo simulation in radiological imaging[J]. IEEE Trans Med Imaging, 2000, 19(5):556-564.
12. ELEKTA C M S. Xio DICOM conformance statement release 4.61[EB/OL] (2010-07-10)[2012-06-12].http://www.elekta.com/healthcare-professionals/products/elekta-software/DICOM-conformance-statements.html.
13. Python Software Foundation. Python v 2.7.3 documentation[EB/OL](2011-06-12)[2012-05-20].http://docs.python.org/2/library/index.html.
14. THOMAS S J. Relative electron density calibration of CT scanners for radiotherapy treatment planning[J]. Br J Radiol, 1999, 72(860):781-786.
15. KHAN, FAIZ M. Treatment planning in radiation oncology[M]. 2nd ed. New York:Lippincott Williams & Wilkins, 2007:64-78.
16. International Atomic Energy Agency. Commissioning of radiotherapy treatment planning systems:testing for typical external beam treatment techniques,IAEA TECDOC 1583[R]. Vienna:IAEA, 2008:35-42.

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