Hybrid systems for reconstruction of freehand 3D ultrasound data

Freehand 3D ultrasound can be acquired without a position sensor by finding the separations of pairs of frames using information in the images themselves. However, small biases in the offset estimates lead to large scale drift in the final reconstruction. In comparison, position sensors have good large scale accuracy, but are inconvenient to use. In this paper, we present methods that combine existing sensorless techniques with limited information from a position sensor, in order to reduce drift errors. We also consider two novel position sensors that are potentially less inconvenient and we assess their accuracy for the purpose of drift correction.

[1]  T. Nelson,et al.  Three-dimensional ultrasound imaging. , 1998, Ultrasound in medicine & biology.

[2]  Richard W Prager,et al.  Subsample interpolation strategies for sensorless freehand 3D ultrasound. , 2006, Ultrasound in medicine & biology.

[3]  G Bashein,et al.  3D ultrasonic image feature localization based on magnetic scanhead tracking: in vitro calibration and validation. , 1994, Ultrasound in medicine & biology.

[4]  J. Brian Fowlkes,et al.  Determination of scan-plane motion using speckle decorrelation: Theoretical considerations and initial test , 1997, Int. J. Imaging Syst. Technol..

[5]  Richard James Housden,et al.  Sensorless freehand 3D ultrasound in real tissue: Speckle decorrelation without fully developed speckle , 2006, Medical Image Anal..

[6]  Lee A. Danisch,et al.  Spatially continuous six degree of freedom position and orientation sensor , 1999 .

[7]  Graham M. Treece,et al.  Engineering a freehand 3D ultrasound system , 2003, Pattern Recognit. Lett..

[8]  Andrew H. Gee,et al.  Distance Measurement for Sensorless 3D US , 2004, MICCAI.

[9]  Andrew H. Gee,et al.  3D ultrasound probe calibration without a position sensor , 2004 .

[10]  R W Prager,et al.  Rapid calibration for 3-D freehand ultrasound. , 1998, Ultrasound in medicine & biology.

[11]  Andrew H. Gee,et al.  Correction of Probe Pressure Artifacts in Freehand 3D Ultrasound , 2001, MICCAI.

[12]  Robert C. Bolles,et al.  Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.

[13]  Thomas Langø,et al.  Probe calibration for freehand 3-D ultrasound. , 2003, Ultrasound in medicine & biology.

[14]  Rachid Aissaoui,et al.  Development and evaluation of a new body-seat interface shape measurement system , 2004, IEEE Transactions on Biomedical Engineering.

[15]  J. J. Moré,et al.  Levenberg--Marquardt algorithm: implementation and theory , 1977 .

[16]  Richard W Prager,et al.  Sensorless reconstruction of unconstrained freehand 3D ultrasound data. , 2007, Ultrasound in medicine & biology.

[17]  J. Edward Swan,et al.  Evaluation of the ShapeTape tracker for wearable, mobile interaction , 2003, IEEE Virtual Reality, 2003. Proceedings..

[18]  Ming Li System and method for 3-D medical imaging using 2-D scan data , 1997 .

[19]  D. Downey,et al.  Three-dimensional ultrasound imaging , 1995, Medical Imaging.

[20]  Laurence Mercier,et al.  A review of calibration techniques for freehand 3-D ultrasound systems. , 2005, Ultrasound in medicine & biology.

[21]  Graham M. Treece,et al.  High-definition freehand 3-D ultrasound. , 2003, Ultrasound in Medicine and Biology.

[22]  P. Carson,et al.  Automated three-dimensional US frame positioning computed from elevational speckle decorrelation. , 1998, Radiology.

[23]  M E Anderson,et al.  Speckle tracking for multi-dimensional flow estimation. , 2000, Ultrasonics.

[24]  Jae Hyun Kim,et al.  US extended-field-of-view imaging technology. , 1997, Radiology.