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Application of Dual Modality Contrast Agent Combined with Multi-Scale Representation in Ultrasound-Magnetic Resonance Imaging Registration Scheme
Authors:Mo Hou  Weiyu Kevin Chiang  Weiqiang Hong  Maoyun Yang  Wenhua Yu
Institution:1 School of Computer Science and Technology, Jiangsu Normal University, Xuzhou, 221116, China2 College of Business, City University of Hong Kong, Hong Kong, 999077, China3 School of Mathematics Science, Jiangsu Normal University, Xuzhou, 221116, China4 Key Laboratory of Education Big Data Science and Engineering, Jiangsu Normal University, Xuzhou, 221116, China
Abstract:To achieve the image registration/fusion and perfect the quality of the integration, with dual modality contrast agent (DMCA), a novel multi-scale representation registration method between ultrasound imaging (US) and magnetic resonance imaging (MRI) is presented in the paper, and how DMCA influence on registration accuracy is chiefly discussed. Owing to US’s intense speckle noise, it is a tremendous challenge to register US with any other modality images. How to improve the algorithms for US processing has become the bottleneck, and in the short term it is difficult to have a breakthrough. In that case, DMCA is employed in both US and MRI to enhance the region of interest. Then, because multi-scale representation is a strategy that attempts to diminish or eliminate several possible local minima and lead to convex optimization problems to be solved quickly and more efficiently, a multi-scale representation Gaussian pyramid based affine registration (MRGP-AR) scheme is constructed to complete the US-MRI registration process. In view of the above-mentioned method, the comparison tests indicate that US-MRI registration/fusion may be a remarkable method for gaining high-quality registration image. The experiments also show that it is feasible that novel nano-materials combined with excellent algorithm are used to solve some hard tasks in medical image processing field.
Keywords:US  MRI  accuracy  registration  DMCA  MRGP-AR
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