Histogram-based optical flow for functional imaging in echocardiography

  • Authors:

  • Sönke Schmid;Daniel Tenbrinck;Xiaoyi Jiang;Klaus Schäfers;Klaus Tiemann;Jörg Stypmann

  • Affiliations:

  • Dept. of Mathematics and Computer Science, University of Münster, Germany and European Institute for Molecular Imaging, Münster, Germany;Dept. of Mathematics and Computer Science, University of Münster, Germany and European Institute for Molecular Imaging, Münster, Germany;Dept. of Mathematics and Computer Science, University of Münster, Germany and European Institute for Molecular Imaging, Münster, Germany;European Institute for Molecular Imaging, Münster, Germany;Dept. of Cardiology and Angiology, University Hospital of Münster, Germany;European Institute for Molecular Imaging, Münster, Germany and Dept. of Cardiology and Angiology, University Hospital of Münster, Germany

  • Venue:
  • CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
  • Year:
  • 2011

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Abstract

Echocardiographic imaging provides various challenges for medical image analysis due to the impact of physical effects in the process of data acquisition. The most significant difference to other medical data is its high level of speckle noise that makes the use of conventional algorithms difficult. Motion analysis on ultrasound (US) data is often referred to as 'Speckle Tracking' which plays an important role in diagnosis and monitoring of cardiovascular diseases and the identification of abnormal cardiac motion. In this paper we address the problem of speckle noise within US images for estimating optical flow. We demonstrate that methods which directly use image intensities are inferior to methods using local features within the US images. Based on this observation we propose an optical flow method which uses histograms as a local feature of US images and show that this approach is more robust under the presence of speckle noise than classical optical flow methods.