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Calibration of an orientation sensor for freehand 3D ultrasound and its use in a hybrid acquisition system.

Housden RJ, Treece GM, Gee AH, Prager RW - Biomed Eng Online (2008)

Bottom Line: In comparison, six degree-of-freedom drift correction was shown to produce excellent reconstructions.A hybrid system incorporating the MT9-B offers an attractive compromise between quality and ease of use.The position sensor is unobtrusive and the system is capable of faithful acquisition, with the one exception of linear drift in the elevational direction.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK. rjh80@eng.cam.ac.uk

ABSTRACT

Background: Freehand 3D ultrasound is a powerful imaging modality with many potential applications. However, its reliance on add-on position sensors, which can be expensive, obtrusive and difficult to calibrate, is a major drawback. Alternatively, freehand 3D ultrasound can be acquired without a position sensor using image-based techniques. Sensorless reconstructions exhibit good fine scale detail but are prone to tracking drift, resulting in large scale geometrical distortions.

Method: We investigate an alternative position sensor, the Xsens MT9-B, which is relatively unobtrusive but measures orientation only. We describe a straightforward approach to calibrating the sensor, and we measure the calibration precision (by repeated calibrations) and the orientation accuracy (using independent orientation measurements). We introduce algorithms that allow the MT9-B potentially to correct both linear and angular drift in sensorless reconstructions.

Results: The MT9-B can be calibrated to a precision of around 1 degrees . Reconstruction accuracy is also around 1 degrees . The MT9-B was able to eliminate angular drift in sensorless reconstructions, though it had little impact on linear drift. In comparison, six degree-of-freedom drift correction was shown to produce excellent reconstructions.

Conclusion: Gold standard freehand 3D ultrasound acquisition requires the synthesis of image-based techniques, for good fine scale detail, and position sensors, for good large scale geometrical accuracy. A hybrid system incorporating the MT9-B offers an attractive compromise between quality and ease of use. The position sensor is unobtrusive and the system is capable of faithful acquisition, with the one exception of linear drift in the elevational direction.

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Principle of elevational speckle decorrelation. The in-plane motion between scans A and B (translation in the x and y directions, roll around the plane normal) is readily determined using conventional 2D image registration techniques. This leaves three degrees of freedom: translation in the elevational direction, tilt (rotation about x) and yaw (rotation about y). Consider corresponding patches in scans A and B (the shaded ellipses). Because of the imperfect elevational focusing, the contents of the patches depend on scatterers within overlapping resolution cells (the hollow ellipsoids) and are therefore correlated. The correlation coefficient depends on the degree of overlap and hence the elevational separation. It follows that, given a suitable decorrelation curve, a measured correlation ρ1 can be used to look up the corresponding separation d1. Repeating this process for three (or more) non-collinear patches determines the out-of-plane separation, tilt and yaw of A relative to B.
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Figure 1: Principle of elevational speckle decorrelation. The in-plane motion between scans A and B (translation in the x and y directions, roll around the plane normal) is readily determined using conventional 2D image registration techniques. This leaves three degrees of freedom: translation in the elevational direction, tilt (rotation about x) and yaw (rotation about y). Consider corresponding patches in scans A and B (the shaded ellipses). Because of the imperfect elevational focusing, the contents of the patches depend on scatterers within overlapping resolution cells (the hollow ellipsoids) and are therefore correlated. The correlation coefficient depends on the degree of overlap and hence the elevational separation. It follows that, given a suitable decorrelation curve, a measured correlation ρ1 can be used to look up the corresponding separation d1. Repeating this process for three (or more) non-collinear patches determines the out-of-plane separation, tilt and yaw of A relative to B.

Mentions: Freehand 3D ultrasound can also be acquired, without a position sensor, by deducing the probe's motion from the B-scan images themselves. Consider two neighbouring B-scans A and B in a freehand sequence. Any in-plane motion between A and B (translation in the axial and lateral directions, roll around the elevational axis) is readily determined using standard 2D image registration techniques [6,7]. Perhaps surprisingly, the out-of-plane motion components can also be estimated from the images [8-10]. This is because the focusing of the ultrasound beam is far from perfect. Consequently, the backscattered signal at any point in a B-scan is a function of the scatterers in a certain resolution cell around that point. The resolution cells are particularly elongated in the elevational direction and there is considerable spatial overlap between cells on neighbouring B-scans – see Figure 1. The echo signals in corresponding patches on A and B are therefore correlated, with the degree of correlation depending on the patches' elevational separation. The correlation between three (non-collinear) pairs of patches can therefore be used to infer the three patch separations and hence the out-of-plane separation, tilt and yaw of A relative to B.


Calibration of an orientation sensor for freehand 3D ultrasound and its use in a hybrid acquisition system.

Housden RJ, Treece GM, Gee AH, Prager RW - Biomed Eng Online (2008)

Principle of elevational speckle decorrelation. The in-plane motion between scans A and B (translation in the x and y directions, roll around the plane normal) is readily determined using conventional 2D image registration techniques. This leaves three degrees of freedom: translation in the elevational direction, tilt (rotation about x) and yaw (rotation about y). Consider corresponding patches in scans A and B (the shaded ellipses). Because of the imperfect elevational focusing, the contents of the patches depend on scatterers within overlapping resolution cells (the hollow ellipsoids) and are therefore correlated. The correlation coefficient depends on the degree of overlap and hence the elevational separation. It follows that, given a suitable decorrelation curve, a measured correlation ρ1 can be used to look up the corresponding separation d1. Repeating this process for three (or more) non-collinear patches determines the out-of-plane separation, tilt and yaw of A relative to B.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2268692&req=5

Figure 1: Principle of elevational speckle decorrelation. The in-plane motion between scans A and B (translation in the x and y directions, roll around the plane normal) is readily determined using conventional 2D image registration techniques. This leaves three degrees of freedom: translation in the elevational direction, tilt (rotation about x) and yaw (rotation about y). Consider corresponding patches in scans A and B (the shaded ellipses). Because of the imperfect elevational focusing, the contents of the patches depend on scatterers within overlapping resolution cells (the hollow ellipsoids) and are therefore correlated. The correlation coefficient depends on the degree of overlap and hence the elevational separation. It follows that, given a suitable decorrelation curve, a measured correlation ρ1 can be used to look up the corresponding separation d1. Repeating this process for three (or more) non-collinear patches determines the out-of-plane separation, tilt and yaw of A relative to B.
Mentions: Freehand 3D ultrasound can also be acquired, without a position sensor, by deducing the probe's motion from the B-scan images themselves. Consider two neighbouring B-scans A and B in a freehand sequence. Any in-plane motion between A and B (translation in the axial and lateral directions, roll around the elevational axis) is readily determined using standard 2D image registration techniques [6,7]. Perhaps surprisingly, the out-of-plane motion components can also be estimated from the images [8-10]. This is because the focusing of the ultrasound beam is far from perfect. Consequently, the backscattered signal at any point in a B-scan is a function of the scatterers in a certain resolution cell around that point. The resolution cells are particularly elongated in the elevational direction and there is considerable spatial overlap between cells on neighbouring B-scans – see Figure 1. The echo signals in corresponding patches on A and B are therefore correlated, with the degree of correlation depending on the patches' elevational separation. The correlation between three (non-collinear) pairs of patches can therefore be used to infer the three patch separations and hence the out-of-plane separation, tilt and yaw of A relative to B.

Bottom Line: In comparison, six degree-of-freedom drift correction was shown to produce excellent reconstructions.A hybrid system incorporating the MT9-B offers an attractive compromise between quality and ease of use.The position sensor is unobtrusive and the system is capable of faithful acquisition, with the one exception of linear drift in the elevational direction.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Engineering, University of Cambridge, Trumpington Street, Cambridge CB2 1PZ, UK. rjh80@eng.cam.ac.uk

ABSTRACT

Background: Freehand 3D ultrasound is a powerful imaging modality with many potential applications. However, its reliance on add-on position sensors, which can be expensive, obtrusive and difficult to calibrate, is a major drawback. Alternatively, freehand 3D ultrasound can be acquired without a position sensor using image-based techniques. Sensorless reconstructions exhibit good fine scale detail but are prone to tracking drift, resulting in large scale geometrical distortions.

Method: We investigate an alternative position sensor, the Xsens MT9-B, which is relatively unobtrusive but measures orientation only. We describe a straightforward approach to calibrating the sensor, and we measure the calibration precision (by repeated calibrations) and the orientation accuracy (using independent orientation measurements). We introduce algorithms that allow the MT9-B potentially to correct both linear and angular drift in sensorless reconstructions.

Results: The MT9-B can be calibrated to a precision of around 1 degrees . Reconstruction accuracy is also around 1 degrees . The MT9-B was able to eliminate angular drift in sensorless reconstructions, though it had little impact on linear drift. In comparison, six degree-of-freedom drift correction was shown to produce excellent reconstructions.

Conclusion: Gold standard freehand 3D ultrasound acquisition requires the synthesis of image-based techniques, for good fine scale detail, and position sensors, for good large scale geometrical accuracy. A hybrid system incorporating the MT9-B offers an attractive compromise between quality and ease of use. The position sensor is unobtrusive and the system is capable of faithful acquisition, with the one exception of linear drift in the elevational direction.

Show MeSH
Related in: MedlinePlus