Takehiro Kajihara1, Takuya Funatomi1, Hiroyuki Kubo1, Takahito Aoto1,
Haruyuki Makishima2, Shigehito Yamada2, Yasuhiro Mukaigawa1
1 Nara Institute of Science and Technology (NAIST), Japan, 2 Kyoto University, Japan


In this research, we propose a novel registration method for three-dimensional (3D) reconstruction from serial section images. 3D reconstructed data from serial section images provides structural information with high resolution. However, there are three problems in 3D reconstruction: non-rigid deformation, tissue discontinuity, and accumulation of scale change. To solve the non-rigid deformation, we propose a novel non-rigid registration method using blending rigid transforms. To avoid the tissue discontinuity, we propose a target image selection method using the criterion based on the blending of transforms. To solve the scale change of tissue, we propose a scale adjustment method using the tissue area before and after registration. The experimental results demonstrate that our method can represent non-rigid deformation with a small number of control points, and is robust to a variation in staining. The results also demonstrate that our target selection method avoids tissue discontinuity and our scale adjustment reduces scale change.


  • T. Kajihara, T. Funatomi, H. Kubo, T. Aoto, H. Makishima, S. Yamada, Y. Mukaigawa
    Feature-Based Non-Rigid Registration of Serial Section Images by Blending Rigid Transformations,
    In The 4th Asian Conference on Pattern Recognition (ACPR 2017)
    • IEEE Xplore
    • Preprint (PDF)
  • T. Kajihara, T. Funatomi, H. Makishima, T. Aoto, H. Kubo, S. Yamada, Y. Mukaigawa
    Non-rigid registration of serial section images by blending transforms for 3D reconstruction,
    In Pattern Recognition, Volume 96, 2019, 106956, ISSN 0031-3203
    • Science Direct
    • Press release
    • プレスリリース