Deformable Image Registration with Automatic Non-Correspondence Detection

  • Kanglin Chen
  • Alexander DerksenEmail author
  • Stefan Heldmann
  • Marc Hallmann
  • Benjamin Berkels
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9087)


Image registration aims at establishing pointwise correspondences between given images. However, in many practical applications, no correspondences can be established in certain parts of the images. A typical example is the tumor resection area in pre- and post-operative medical images. In this paper, we introduce a novel variational framework that combines registration with an automatic detection of non-correspondence regions. The formulation of the proposed approach is simple but efficient, and compatible with a large class of image registration similarity measures and regularizers. The resulting minimization problem is solved numerically with a non-alternating gradient flow scheme. Furthermore, the method is validated on synthetic data as well as axial slices of pre-, post- and intra-operative MR T1 head scans.


Joint method Image registration Segmentation Level set Non-correspondence detection Lesion Resection 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Kanglin Chen
    • 1
  • Alexander Derksen
    • 1
    Email author
  • Stefan Heldmann
    • 1
  • Marc Hallmann
    • 1
  • Benjamin Berkels
    • 2
  1. 1.Fraunhofer MEVIS Project Group Image RegistrationLübeckGermany
  2. 2.AICESRWTH Aachen UniversityAachenGermany

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