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Focal Liver Lesion Tracking in CEUS for Characterisation Based on Dynamic Behaviour

  • Spyridon Bakas
  • Andreas Hoppe
  • Katerina Chatzimichail
  • Vasileios Galariotis
  • Gordon Hunter
  • Dimitrios Makris
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7431)

Abstract

This paper presents a methodology for tracking a hypo- or hyper-enhanced focal liver lesion (FLL) and a healthy liver region in a video sequence of a Contrast-Enhanced Ultrasound (CEUS) examination. The outcome allows the differentiation between benign and malignant cases, by characterising FLLs of typical behaviour, according to their Time-Intensity curves. The task is challenging mainly due to intensity changes caused by contrast agents. Initially the ultrasound mask is automatically localised and then the FLL and parenchyma regions are tracked, assuming affine transformations on the image plane, employing the point-based registration technique of Lowe’s scale-invariant feature transform (SIFT) keypoints detector. Finally, a quantitative evaluation of the tracking process provides a confidence measure for the characterisation decision.

Keywords

Ground Truth Focal Liver Lesion Generalise Procrustes Analysis Keypoints Detector CEUS Examination 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Spyridon Bakas
    • 1
  • Andreas Hoppe
    • 1
  • Katerina Chatzimichail
    • 2
  • Vasileios Galariotis
    • 2
  • Gordon Hunter
    • 1
  • Dimitrios Makris
    • 1
  1. 1.Digital Imaging Research Centre, School of Computing and Information Systems, Faculty of Science, Engineering and ComputingKingston UniversityLondonUnited Kingdom
  2. 2.Radiology & Imaging Research CenterUniversity of Athens, Evgenidion HospitalAthensGreece

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