Probabilistic speckle decorrelation for 3D ultrasound

Authors:
Catherine Laporte;Tal Arbel
Affiliations:
Centre for Intelligent Machines, McGill University, Montréal, Canada;Centre for Intelligent Machines, McGill University, Montréal, Canada
Venue:
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Year:
2007

Citing 2
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Decompression and speckle detection for ultrasound images using the homodyned K-distribution

Pattern Recognition Letters - Speciqal issue: Ultrasonic image processing and analysis

Real-time Motion Stabilization with B-mode Ultrasound Using Image Speckle Information and Visual Servoing

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Abstract

Recent developments in freehand 3D ultrasound (US) have shown how image registration and speckle decorrelation methods can be used for 3D reconstruction instead of relying on a tracking device. Estimating elevational separation between untracked US images using speckle decorrelation is error prone due to the uncertainty that plagues the correlation measurements. In this paper, using maximum entropy estimation methods, the uncertainty is directly modeled from the calibration data normally used to estimate an average decorrelation curve. Multiple correlation measurements can then be fused within a maximum likelihood estimation framework in order to reduce the drift in elevational pose estimation over large image sequences. The approach is shown to be effective through empirical results on simulated and phantom US data.