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Computer Vision Elastography: Speckle adaptive motion estimation for elastography using ultrasound sequences

James Revell, Majid Mirmehdi, Donal McNally, Computer Vision Elastography: Speckle adaptive motion estimation for elastography using ultrasound sequences. IEEE Transactions on Medical Imaging, 24(6), pp. 755–766. June 2005. PDF, 912 Kbytes.

Abstract

We present the development and validation of an image based speckle tracking methodology, for determining temporal 2D axial and lateral displacement and strain fields from ultrasound video streams. We refine a multiple scale region matching approach incorporating novel solutions to known speckle tracking problems. Key contributions include automatic similarity measure selection to adapt to varying speckle density, quantifying trajectory fields and spatio-temporal elastograms. Results are validated using tissue mimicking phantoms and \emph{in vitro} data, before applying them to \emph{in vivo} musculoskeletal ultrasound sequences. The method presented has the potential to improve clinical knowledge of tendon pathology from carpel tunnel syndrome, inflammation from implants, sport injuries, and many others.

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