Joint CT/CBCT deformable registration and CBCT enhancement for cancer radiotherapy

被引:30
作者
Lou, Yifei [1 ,2 ]
Niu, Tianye [3 ,4 ]
Jia, Xun [5 ,6 ]
Vela, Patricio A. [1 ,2 ]
Zhu, Lei [3 ,4 ]
Tannenbaum, Allen R. [7 ,8 ,9 ]
机构
[1] Georgia Inst Technol, Sch Elect, Atlanta, GA 30332 USA
[2] Georgia Inst Technol, Sch Comp Engn, Atlanta, GA 30332 USA
[3] Georgia Inst Technol, Nucl & Radiol Engn Programs, George W Woodruff Sch Mech Engn, Atlanta, GA 30332 USA
[4] Georgia Inst Technol, Med Phys Programs, George W Woodruff Sch Mech Engn, Atlanta, GA 30332 USA
[5] Univ Calif San Diego, Ctr Adv Radiotherapy Technol, La Jolla, CA 92037 USA
[6] Univ Calif San Diego, Dept Radiat Oncol, La Jolla, CA 92037 USA
[7] Boston Univ, Dept Elect, Boston, MA 02215 USA
[8] Boston Univ, Dept Comp, Boston, MA 02215 USA
[9] Boston Univ, Dept Biomed Engn, Boston, MA 02215 USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
Deformable image registration; Multimodal registration; Mutual information; Shading correction; Scatter removal; CONE-BEAM CT; X-RAY SCATTER; IMAGE REGISTRATION; PLANNING CT; RADIATION-THERAPY; NONRIGID REGISTRATION; SHADING CORRECTION; SEGMENTATION; ALGORITHM; IMPLEMENTATION;
D O I
10.1016/j.media.2013.01.005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper details an algorithm to simultaneously perform registration of computed tomography (CT) and cone-beam computed (CBCT) images, and image enhancement of CBCT. The algorithm employs a viscous fluid model which naturally incorporates two components: a similarity measure for registration and an intensity correction term for image enhancement. Incorporating an intensity correction term improves the registration results. Furthermore, applying the image enhancement term to CBCT imagery leads to an intensity corrected CBCT with better image quality. To achieve minimal processing time, the algorithm is implemented on a graphic processing unit (CPU) platform. The advantage of the simultaneous optimization strategy is quantitatively validated and discussed using a synthetic example. The effectiveness of the proposed algorithm is then illustrated using six patient datasets, three head-and-neck datasets and three prostate datasets. Published by Elsevier B.V.
引用
收藏
页码:387 / 400
页数:14
相关论文
共 51 条
[31]   POLYNOMIAL INTENSITY CORRECTION FOR MULTIMODAL IMAGE REGISTRATION [J].
Ou, Wanmei ;
Chefd'Hotel, Christophe .
2009 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO, VOLS 1 AND 2, 2009, :939-+
[32]   Multiscale registration of planning CT and daily cone beam CT images for adaptive radiation therapy [J].
Paquin, Dana ;
Levy, Doron ;
Xing, Lei .
MEDICAL PHYSICS, 2009, 36 (01) :4-11
[33]   Mutual-information-based registration of medical images: A survey [J].
Pluim, JPW ;
Maintz, JBA ;
Viergever, MA .
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2003, 22 (08) :986-1004
[34]  
Pohl KM, 2005, LECT NOTES COMPUT SC, V3749, P310
[35]   Computation of Image Spatial Entropy Using Quadrilateral Markov Random Field [J].
Razlighi, Qolamreza R. ;
Kehtarnavaz, Nasser ;
Nosratinia, Aria .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2009, 18 (12) :2629-2639
[36]  
Roche A, 1998, LECT NOTES COMPUT SC, V1496, P1115, DOI 10.1007/BFb0056301
[37]   High performance computing for deformable image registration:: Towards a new paradigm in adaptive radiotherapy [J].
Samant, Sanjiv S. ;
Xia, Junyi ;
Muyan-Oezcelilk, Pinar ;
Owens, John D. .
MEDICAL PHYSICS, 2008, 35 (08) :3546-3553
[38]   Image interpolation in 4D CT using a BSpline deformable registration model [J].
Schreibmann, E ;
Chen, GTY ;
Xing, L .
INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2006, 64 (05) :1537-1550
[39]  
Shams R., 2010, SIGNAL PROCESS MAG, V27
[40]   GPU-based streaming architectures for fast cone-beam CT image reconstruction and demons deformable registration [J].
Sharp, G. C. ;
Kandasamy, N. ;
Singh, H. ;
Folkert, M. .
PHYSICS IN MEDICINE AND BIOLOGY, 2007, 52 (19) :5771-5783