Vascular Registration in Photoacoustic Imaging by Low-Rank Alignment via Foreground, Background and Complement Decomposition
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.
KeywordsDense Noise Nuclear Norm Augmented Lagrange Multiplier Difference Component Coarse Alignment
This work was funded by ImPACT Program of Council for Science, Technology and Innovation (Cabinet Office, Government of Japan).
- 4.Frangi, A.F., Niessen, W.J., Vincken, K.L., Viergever, M.A.: Multiscale vessel enhancement filtering. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MICCAI 1998. LNCS, vol. 1496, pp. 130–137. Springer, Heidelberg (1998)Google Scholar
- 10.Liu, X., Niethammer, M., Kwitt, R., McCormick, M., Aylward, S.: Low-rank to the rescue – atlas-based analyses in the presence of pathologies. In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds.) MICCAI 2014, Part III. LNCS, vol. 8675, pp. 97–104. Springer, Heidelberg (2014)Google Scholar
- 11.Baghaie, A., D’souza, R.M., Yu, Z.: Sparse and low rank decomposition based batch image alignment for speckle reduction of retinal oct images, ISBI, pp. 226–230 (2015)Google Scholar
- 13.Lin, Z., Chen, M., Wu, L., Ma, Y.: The augmented Lagrange multiplier method for exact recovery of corrupted low-rank matrices, UIUC Technical report UILU-ENG-09-2215 (2009)Google Scholar