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Rigid Image Registration Based on Graph Matching

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Advances in Artificial Intelligence and Security (ICAIS 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1422))

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Abstract

Medical image registration is an important technology in medical image processing and analysis. It has important application value in guiding radiotherapy, radiosurgery, minimally invasive surgery, endoscopy, and interventional radiology. Rigidly aligning two images is used to register rigid body structure, and it is also usually the first step for deformable registration with a large discrepancy. In the field of computer vision, one well-established method for image alignment is to find corresponding points from two images, and image alignment is based on identified corresponding points. Our approach lies in this category. Feature matching is crucial in finding corresponding points. However, conventional feature matching, such as SIFT, fails to consider the structural information between features. In this paper, a rigid image registration algorithm based on hypergraph matching is proposed. First, perform rough matching feature through SIFT (Scale invariant feature transform); then, based on coarse feature matching, filter out abnormal points through the hypergraph matching method that considers the structural information between features to obtain the correct feature matching pair; finally pass the obtained feature matching is registered to the calculated conversion matrix. Experimental results show that this method's registration results are better than those of SIFT and MIND methods regardless of whether it is rotated or scaled.

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Funding

This work is supported in part by the Introduction Talent Research Start-up Pro-gram of Chengdu University of Information Technology (No. KYTZ202008), and in part by the Sichuan Science and Technology Program (2019YFH0085, 2019ZDZX0005, 2019YFG0196), and in part by the Science and Technology Project Affiliated to the Education Department of Chongqing Municipality (No. 19ZB0257).

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Authors and Affiliations

  1. Department of Computer Science, Chengdu University of Information Technology, Chengdu, 610225, China

    Zhiqin Lei, Jinrong Hu & Bin Ye

Authors
  1. Zhiqin Lei
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  2. Jinrong Hu
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  3. Bin Ye
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Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Xiaorui Zhang

  3. Jinan University, Guangzhou, China

    Zhihua Xia

  4. Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Lei, Z., Hu, J., Ye, B. (2021). Rigid Image Registration Based on Graph Matching. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Advances in Artificial Intelligence and Security. ICAIS 2021. Communications in Computer and Information Science, vol 1422. Springer, Cham. https://doi.org/10.1007/978-3-030-78615-1_26

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  • DOI: https://doi.org/10.1007/978-3-030-78615-1_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78614-4

  • Online ISBN: 978-3-030-78615-1

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