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Medical Ultrasound Image Similarity Measurement by Human Visual System (HVS) Modelling

  • Darryl de Cunha
  • Leila Eadie
  • Benjamin Adams
  • David Hawkes
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2525)

Abstract

We applied a four stage model of human vision to the problem of similarity measurement of medical (liver) ultrasound images. The results showed that when comparing a given image to a set that contained images with similar features, the model was able to correctly identify the most similar image in the set. Additionally, the shape of the similarity function closely followed a subjective measure of visual similarity for images around the best match. Removing some computational steps to reduce processing time enabled the comparison method to run in near real-time (< 5 seconds), but with some acceptable loss of accuracy. These results could not be achieved using conventional similarity measurements based on image grey level statistics.

Keywords

Ultrasound Image Vision Research Human Visual System Comparison Image Gabor Analysis 
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 2002

Authors and Affiliations

  • Darryl de Cunha
    • 1
  • Leila Eadie
    • 2
  • Benjamin Adams
    • 1
  • David Hawkes
    • 1
  1. 1.Division of ImagingGuy’s Hospital, King’s College LondonLondonUK
  2. 2.Department of Surgery and Liver TransplantationRoyal Free HospitalHampstead, LondonUK

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