Shortest path refinement for motion estimation from tagged MR images

Xiaofeng Liu, Jerry L. Prince

Research output: Contribution to journalArticlepeer-review


Magnetic resonance tagging makes it possible to measure the motion of tissues such as muscles in the heart and tongue. The harmonic phase (HARP) method largely automates the process of tracking points within tagged MR images, permitting many motion properties to be computed. However, HARP tracking can yield erroneous motion estimates due to 1) large deformations between image frames, 2) through-plane motion, and 3) tissue boundaries. Methods that incorporate the spatial continuity of motionso-called refinement or flood-filling methodshave previously been reported to reduce tracking errors. This paper presents a new refinement method based on shortest path computations. The method uses a graph representation of the image and seeks an optimal tracking order from a specified seed to each point in the image by solving a single source shortest path problem. This minimizes the potential errors for those path dependent solutions that are found in other refinement methods. In addition to this, tracking in the presence of through-plane motion is improved by introducing synthetic tags at the reference time (when the tissue is not deformed). Experimental results on both tongue and cardiac images show that the proposed method can track the whole tissue more robustly and is also computationally efficient.

Original languageEnglish (US)
Article number5432997
Pages (from-to)1560-1572
Number of pages13
JournalIEEE transactions on medical imaging
Issue number8
StatePublished - Aug 2010


  • Dijkstra's algorithm
  • harmonic phase (HARP)
  • magnetic resonance (MR) tagging
  • motion tracking
  • shortest path

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering


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