4.7 Article

Incorporation of Structural Tensor and Driving Force Into Log-Demons for Large-Deformation Image Registration

Journal

IEEE TRANSACTIONS ON IMAGE PROCESSING
Volume 28, Issue 12, Pages 6091-6102

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIP.2019.2924168

Keywords

Image registration; tensor; driving force; Log-Demons algorithm; optimization

Funding

  1. National Nature Science Foundation of China [61773166, 61772369]
  2. Natural Science Foundation of Shanghai [17ZR1408200]
  3. Science and Technology Commission of Shanghai Municipality [14DZ2260800]
  4. National Science Foundation of China [U18092006]
  5. Changjiang Scholars Program of China
  6. Shanghai Science and Technology Committee [17411953100, 16JC1401300]
  7. Shanghai Municipal Science and Technology Committee of Shanghai Outstanding Academic Leaders Plan [19XD1434000]

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Large-deformation image registration is important in theory and application in computer vision, but is a difficult task for non-rigid registration methods. In this paper, we propose a structural Tensor and Driving force-based Log-Demons algorithm for it, named TDLog-Demons for short. The structural tensor of an image is proposed to obtain a highly accurate deformation field. The driving force is proposed to solve the registration issue of large-deformation that often causes Log-Demons to trap into local minima. It is defined as a point correspondence obtained via multisupport-region-order-based gradient histogram descriptor matching on image's boundary points. It is integrated into an exponentially decreasing form with the velocity field of Log-Demons to move the points accurately and to speed up a registration process. Consequently, the driving force-based Log-Demons can well deal with large-deformation image registration. Extensive experiments demonstrate that the TDLog-Demons not only captures large deformations at a high accuracy but also yields a smooth deformation.

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