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Vascular Registration in Photoacoustic Imaging by Low-Rank Alignment via Foreground, Background and Complement Decomposition

  • Ryoma Bise
  • Yingqiang Zheng
  • Imari Sato
  • Masakazu Toi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9902)

Abstract

Photoacoustic (PA) imaging has been gaining attention as a new imaging modality that can non-invasively visualize blood vessels inside biological tissues. In the process of imaging large body parts through multi-scan fusion, alignment turns out to be an important issue, since body motion degrades image quality. In this paper, we carefully examine the characteristics of PA images and propose a novel registration method that achieves better alignment while effectively decomposing the shot volumes into low-rank foreground (blood vessels), dense background (noise), and sparse complement (corruption) components on the basis of the PA characteristics. The results of experiments using a challenging real data-set demonstrate the efficacy of the proposed method, which significantly improved image quality, and had the best alignment accuracy among the state-of-the-art methods tested.

Keywords

Dense Noise Nuclear Norm Augmented Lagrange Multiplier Difference Component Coarse Alignment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work was funded by ImPACT Program of Council for Science, Technology and Innovation (Cabinet Office, Government of Japan).

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Ryoma Bise
    • 1
  • Yingqiang Zheng
    • 1
  • Imari Sato
    • 1
  • Masakazu Toi
    • 2
  1. 1.National Institute of InformaticsChiyodaJapan
  2. 2.Kyoto University HospitalKyotoJapan

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