Kinect-Based Automatic Spatial Registration Framework for Neurosurgical Navigation

开云网页登录学报（英文版）››2014,Vol. 19››Issue (5): 617-623.doi:10.1007/s12204-014-1550-2

Kinect-Based Automatic Spatial Registration Framework for Neurosurgical Navigation

ZHANG Li-xia1 (张丽霞), ZHANG Shao-ting2 (张少霆), XIE Hong-zhi3 (谢洪智),ZHUANG Xia-hai4 (庄吓海), GU Li-xu1* (顾力栩)

(1. School of Biomedical Engineering, Shanghai Jiaotong University, Shanghai 200030, China; 2. Department of Computer Science, University of North Carolina at Charlotte, NC 28223, USA; 3. Peking Union Medical College Hospital, Beijing 100730, China; 4. Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China)

出版日期:2014-10-31发布日期:2014-11-12
通讯作者:GU Li-xu (顾力栩) E-mail:gulixu@sjtu.edu.cn

Kinect-Based Automatic Spatial Registration Framework for Neurosurgical Navigation

ZHANG Li-xia1 (张丽霞), ZHANG Shao-ting2 (张少霆), XIE Hong-zhi3 (谢洪智),ZHUANG Xia-hai4 (庄吓海), GU Li-xu1* (顾力栩)

(1. School of Biomedical Engineering, Shanghai Jiaotong University, Shanghai 200030, China; 2. Department of Computer Science, University of North Carolina at Charlotte, NC 28223, USA; 3. Peking Union Medical College Hospital, Beijing 100730, China; 4. Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210, China)

Online:2014-10-31Published:2014-11-12
Contact:GU Li-xu (顾力栩) E-mail:gulixu@sjtu.edu.cn

摘要/Abstract

摘要：As image-guided navigation plays an important role in neurosurgery, the spatial registration mapping the pre-operative images with the intra-operative patient position becomes crucial for a high accurate surgical output. Conventional landmark-based registration requires expensive and time-consuming logistic support. Surface-based registration is a plausible alternative due to its simplicity and efficacy. In this paper, we propose a comprehensive framework for surface-based registration in neurosurgical navigation, where Kinect is used to automatically acquire patient’s facial surface in a real time manner. Coherent point drift (CPD) algorithm is employed to register the facial surface with pre-operative images (e.g., computed tomography (CT) or magnetic resonance imaging (MRI)) using a coarse-to-fine scheme. The spatial registration results of 6 volunteers demonstrate that the proposed framework has potential for clinical use.

关键词:surface-based registration,neurosurgical navigation,coherent point drift (CPD)

Abstract:As image-guided navigation plays an important role in neurosurgery, the spatial registration mapping the pre-operative images with the intra-operative patient position becomes crucial for a high accurate surgical output. Conventional landmark-based registration requires expensive and time-consuming logistic support. Surface-based registration is a plausible alternative due to its simplicity and efficacy. In this paper, we propose a comprehensive framework for surface-based registration in neurosurgical navigation, where Kinect is used to automatically acquire patient’s facial surface in a real time manner. Coherent point drift (CPD) algorithm is employed to register the facial surface with pre-operative images (e.g., computed tomography (CT) or magnetic resonance imaging (MRI)) using a coarse-to-fine scheme. The spatial registration results of 6 volunteers demonstrate that the proposed framework has potential for clinical use.

Key words:surface-based registration,neurosurgical navigation,coherent point drift (CPD)

中图分类号:

TP 391.7

ZHANG Li-xia1 (张丽霞), ZHANG Shao-ting2 (张少霆), XIE Hong-zhi3 (谢洪智),ZHUANG Xia-hai4. Kinect-Based Automatic Spatial Registration Framework for Neurosurgical Navigation[J]. 开云网页登录学报（英文版）, 2014, 19(5): 617-623.

ZHANG Li-xia1 (张丽霞), ZHANG Shao-ting2 (张少霆), XIE Hong-zhi3 (谢洪智),ZHUANG Xia-hai4 (庄吓海), GU Li-xu1* (顾力栩). Kinect-Based Automatic Spatial Registration Framework for Neurosurgical Navigation[J]. Journal of shanghai Jiaotong University (Science), 2014, 19(5): 617-623.

参考文献

[1] Peters T M. Image-guidance for surgical procedures[J]. Physics in Medicine and Biology, 2006, 51(14):R505-R540.
[2] Maurer Jr C R, Maciunas R J, Michael Fitzpatrick J. Registration of head CT images to physical space using a weighted combination of points and surfaces [J]. IEEE Transactions on Medical Imaging,1998, 17(5): 753-761.
[3] Marmulla R, Hassfeld S, L¨uth T, et al. Laserscan-based navigation in cranio-maxillofacial surgery[J]. Journal of Cranio-Maxillofacial Surgery, 2003,31(5): 267-277.
[4] Hoffmann J, Westendorff C, Leitner C, et al.Validation of 3D-laser surface registration for imageguided cranio-maxillofacial surgery [J]. Journal of Cranio-Maxillofacial Surgery, 2005, 33(1): 13-18.
[5] Eggers G, M¨uhling J, Marmulla R. Image-topatient registration techniques in head surgery [J]. International Journal of Oral and Maxillofacial Surgery,2006, 35(12): 1081-1095.
[6] Khoshelham K, Elberink S O. Accuracy and resolution of Kinect depth data for indoor mapping applications[J]. Sensors, 2012, 12(2): 1437-1454.
[7] Berger K, Ruhl K, Schroeder Y, et al. Markerless motion capture using multiple color-depth sensors [C]// Vision Modeling Visualization. Bangor, Wales:Eurographics Association, 2011: 317-324.
[8] Otsu N. A threshold selection method from gray-level histograms [J]. IEEE Transactions on Systems, Man,and Cybernetics, 1979, 9(1): 62-66.
[9] Li H, Shen T, Huang X. Approximately global optimization for robust alignment of generalized shapes [J].IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011, 33(6): 1116-1131.
[10] Jian B, Vemuri B C. Robust point set registration using Gaussian mixture models [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011,33(8): 1633-1645.
[11] Zhang S, Zhan Y, Dewan M, et al. Towards robust and effective shape modeling: Sparse shape composition[J]. Medical Image Analysis, 2012, 16(1): 265-277.
[12] Zhang S, Zhan Y, Cui X, et al. 3D anatomical shape atlas construction using mesh quality preserved deformable models [J]. Computer Vision and Image Understanding,2013, 117(9): 1061-1071.
[13] Myronenko A, Song X. Point set registration: Coherent point drift [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(12):2262-2275.
[14] Salvi J, Matabosch C, Fofi D, et al. A review of recent range image registration methods with accuracy evaluation [J]. Image and Vision Computing,2007, 25(5): 578-596.
[15] Hernandez M, Choi J, Medioni G. Laser scan quality 3-D face modeling using a low-cost depth camera[C]// 20th European Signal Processing Conference.Bucharest, Romania: IEEE, 2012: 1995-1999.
[16] Meyer G P, Do M N. Real-time 3D face modeling with a commodity depth camera [C]// 2013 IEEE International Conference on Multimedia and Expo Workshops.San Jose, CA: IEEE, 2013: 1-4.

Kinect-Based Automatic Spatial Registration Framework for Neurosurgical Navigation

Kinect-Based Automatic Spatial Registration Framework for Neurosurgical Navigation

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