Abstract
Purpose
In this paper, we present a method to remove system induced geometric distortions in MR images.
Methods
A large 3D phantom with spherical balls was used to characterize geometric distortion on an AIRIS Mate 0.2 T MR Scanner (Hitachi). MR images of the phantom were acquired in axial, sagittal planes. Using 2D Fast Spin Echo (FSE) sequence, distortions were measured at each control point. Two piecewise interpolation methods were then applied to correct distortions and greyvalues.
Results
The distortion was reduced from 16 to 1.2 mm at 180 mm from the magnet center.
Conclusion
Distortions were characterized and corrected in any axial, sagittal or coronal slice within an effective FOV of 330(LR) × 180(AP) × 210(HF) mm3. A fast and accurate method for correction of geometric distortion was performed within large distances from the magnet isocenter.
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Fransson A, Andreo P, Potter R (2001) Aspects of MR image distortions in radiotherapy treatment planning. Strahlenther onkol 177(2): 59–73
Mah D, Steckner M, Palacio E, Mitra R, Richardson T, Hanks GE (2002) Characteristics and quality assurance of a dedicated open 0.23 T MRI for radiation therapy simulation. Med Phys 29(11): 2541–2547
Krempien RC, Schubert K, Zierhut D, Steckner MC, Treiber M, Harms W, Mende U, Latz D, Wannenmacher M, Wenz F (2002) Open low-field magnetic resonance imaging in radiation therapy treatment planning. Int J Radiat Oncol Biol Phys 53(5): 1350–1360
Jackson ASN, Reinsberg SA, Sohaib SA, Charles-Edwards EM, Mangar SA, South CP, Leach MO, Dearnaley DP (2007) Distortion-corrected t2 weighted MRI: a novel approach to prostate radiotherapy planning. Br J Radiol 80(959): 926
Pasquier D, Lacornerie T, Vermandel M, Rousseau J, Lartigau E, Betrouni N (2007) Automatic segmentation of pelvic structures from magnetic resonance images for prostate cancer radiotherapy. Int J Radiat Oncol Biol Phys 68(2): 592–600
Blanco RT, Ojala R, Kariniemi J, Perala J, Niinimaki J, Tervonen O (2005) Interventional and intraoperative MRI at low field scanner—a review. Eur J Radiol 56(2): 130–142
Elgort DR, Duerk JL (2005) A review of technical advances in interventional magnetic resonance imaging. Acad Radiol 12(9): 1089–1099
Sequeiros RB, Ojala R, Kariniemi J, Perala J, Niinimaki J, Reinikainen H, Tervonen O (2005) MR-guided interventional procedures: a review. Acta Radiol 46(6): 576–586
Viard R, Rousseau J (2008) Imagerie interventionnelle par résonance magnétique: Etat de l’art des développements techniques. J de Radiol 89: 13–20
Viard R, Betrouni N, Rousseau J, Mordon S, Ernst O, Maouche S (2007) Needle positioning in interventional MRI procedure: real time optical localisation and accordance with the roadmap. Conf Proc IEEE Eng Med Biol Soc 2748–2751. doi:10.1109/IEMBS.2007.4352897
Michiels J, Bosmans H, Pelgrims P, Vandermeulen D, Gybels J, Marchal G, Suetens P (1994) On the problem of geometric distortion in magnetic resonance images for stereotactic neurosurgery. Magn Reson Imaging 12(5): 749–765
Daanen V, Coste E, Sergent G, Godart F, Vasseur C, Rousseau J (2000) Accurate localization of needle entry point in interventional MRI. J Magn Reson Imaging 12(4): 645–649
Breeuwer M, Holden M, Zylka W (2001) Detection and correction of geometric distortion in 3D MR images. Proc SPIE 4322: 1110–1120
Petersch B, Bogner J, Fransson A, Lorang T, Potter R (2004) Effects of geometric distortion in 0.2 T MRI on radiotherapy treatment planning of prostate cancer. Radiother Oncol 71(1): 55–64
Wang D, Doddrell DM (2005) Geometric distortion in structural magnetic resonance imaging current. Med Imaging Rev 1(1): 49–60
Chen Z, Ma CM, Paskalev K, Li J, Yang J, Richardson T, Palacio L, Xu X, Chen L (2006) Investigation of MR image distortion for radiotherapy treatment planning of prostate cancer. Phys Med Biol 51(6): 1393–1403
Otsu N (1975) A threshold selection method from gray-level histograms. Automatica 11: 285–296
Chen T, Wu QH, Rahmani-Torkaman R, Hughes J (2002) A pseudo top-hat mathematical morphological approach to edge detection in dark regions. Pattern Recognition. 35(1): 199–210. doi:10.1016/S0031-3203(01)00024-3
Besl PJ, McKay ND (1992) a method for registration of 3D shapes. IEEE Trans Pattern Anal Mach Intell 14(2): 239–256
Franke R (1982) Scattered data interpolation: tests of some methods. Math Comput 38: 181–200
De Boor C (1979) Efficient computer manipulation of tensor products. ACM Trans Math Softw (toms) 5(2): 173–182
Keys R (1981) Cubic convolution interpolation for digital image processing. Acoustics, Speech, and Signal Processing [see also ieee transactions on signal processing]. IEEE Trans 29(6): 1153–1160
Doran SJ, Charles-Edwards L, Reinsberg SA, Leach MO (2005) A complete distortion correction for MR images: I Gradient warp correction. Phys Med Biol 50(7): 1343–1361
Wang D, Doddrell DM, Cowin G (2004) A novel phantom and method for comprehensive 3Dimensional measurement and correction of geometric distortion in magnetic resonance imaging. Magn Reson Imaging 22(4): 529–542
Fritsch FN, Butland J (1984) A method for constructing local monotone piecewise cubic interpolants. SIAM J Sci Stat Comput 5: 300–304
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Viard, R., Mordon, S., Betrouni, N. et al. Correction of images in an open-configuration MR imaging system for radiation therapy planning and Interventional MRI. Int J CARS 3, 283–289 (2008). https://doi.org/10.1007/s11548-008-0224-7
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DOI: https://doi.org/10.1007/s11548-008-0224-7