Measurement selection in untracked freehand 3D ultrasound

In freehand 3D ultrasound, out-of-plane transducer motion can be estimated via speckle decorrelation instead of using a position tracking device. This approach was recently adapted to arbitrary media by predicting elevational decorrelation curves from local image statistics. However, such adaptive models tend to yield biased measurements in the presence of spatially persistent structures. To account for such failures, this paper introduces a new iterative algorithm for probabilistic fusion and selection of correlation measurements. In experiments with imagery of animal tissue, the approach yields significant accuracy improvements over alternatives which do not apply principled measurement selection.