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Proceedings Paper

Accurate CT-ultrasound image registration using simulated transformation optimization
Author(s): Weijian Cong; Xiaohui Liang; Jiahui Dong; Danni Ai; Jingfan Fan; Jian Yang
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Paper Abstract

The accuracy of ultrasound/computed tomography (CT) image registration is the key to ultrasound-guided intervention. Thus, the aim of this study is to address the limitation of current image similarity measures to evaluate the accuracy of ultrasound/CT image registration correctly. In this study, an ultrasound/CT image registration method based on simulated transformation optimization is presented. The approach initially preprocesses the ultrasound/CT images for registration through the tensor principal component analysis method to reduce the influence of noise on registration accuracy. Multiscale enhancement algorithm is also adopted to enhance the tubular structures of the CT images. Simulated transformation optimization based on the CT images is then provided. Afterward, given the ultrasonic imaging parameter estimates, the method captures a CT section to obtain ultrasonic images by simulation. The ultrasonic simulation is introduced into the image similarity measure, and the simulation transformation correlation measure is established. The transformation matrix is optimized by the conjugate direction acceleration algorithm to realize the fast and accurate registration of the ultrasound/CT image. Experimental results demonstrate that when Correlation of Simulation Transformation is employed as the similarity measure, the variation range of the six parameters in the transformation matrix is ±0.01, and the ultrasound/CT image registration method based on simulated transformation optimization can rapidly and accurately register ultrasound/CT images. The accurate registration of ultrasound/CT images enables the combination between real-time ultrasonic images and preoperative CT images. Hence, it has the potential to be utilized for ultrasound-guided surgical navigation in clinical practice.

Paper Details

Date Published: 14 August 2019
PDF: 6 pages
Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111790V (14 August 2019); doi: 10.1117/12.2539744
Show Author Affiliations
Weijian Cong, BeiHang Univ. (China)
Xiaohui Liang, BeiHang Univ. (China)
Jiahui Dong, Beijing Institute of Technology (China)
Danni Ai, Beijing Institute of Technology (China)
Jingfan Fan, BeiHang Univ. (China)
Jian Yang, Beijing Institute of Technology (China)


Published in SPIE Proceedings Vol. 11179:
Eleventh International Conference on Digital Image Processing (ICDIP 2019)
Jenq-Neng Hwang; Xudong Jiang, Editor(s)

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