Supervoxel Classification Forests for Estimating Pairwise Image Correspondences

  • Fahdi KanavatiEmail author
  • Tong Tong
  • Kazunari Misawa
  • Michitaka Fujiwara
  • Kensaku Mori
  • Daniel Rueckert
  • Ben Glocker
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9352)


This paper proposes a general method for establishing pairwise correspondences, which is a fundamental problem in image analysis. The method consists of over-segmenting a pair of images into supervoxels. A forest classifier is then trained on one of the images, the source, by using supervoxel indices as voxelwise class labels. Applying the forest on the other image, the target, yields a supervoxel labelling which is then regularized using majority voting within the boundaries of the target’s supervoxels. This yields semi-dense correspondences in a fully automatic, efficient and robust manner. The advantage of our approach is that no prior information or manual annotations are required, making it suitable as a general initialisation component for various medical imaging tasks that require coarse correspondences, such as, atlas/patch-based segmentation, registration, and atlas construction. Our approach is evaluated on a set of 150 abdominal CT images. In this dataset we use manual organ segmentations for quantitative evaluation. In particular, the quality of the correspondences is determined in a label propagation setting. Comparison to other state-of-the-art methods demonstrate the potential of supervoxel classification forests for estimating image correspondences.


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© Springer International Publishing Switzerland 2015

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Authors and Affiliations

  • Fahdi Kanavati
    • 1
    Email author
  • Tong Tong
    • 1
  • Kazunari Misawa
    • 2
  • Michitaka Fujiwara
    • 3
  • Kensaku Mori
    • 4
  • Daniel Rueckert
    • 1
  • Ben Glocker
    • 1
  1. 1.Biomedical Image Analysis Group, Department of ComputingImperial College LondonLondonUK
  2. 2.Aichi Cancer CenterNagoyaJapan
  3. 3.Nagoya University HospitalNagoyaJapan
  4. 4.Information and CommunicationsNagoya UniversityNagoyaJapan

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