Object identification accuracy under ultrasound enhanced virtual reality for minimally invasive cardiac surgery

Andrew D. Wiles; John Moore; Cristian A. Linte; Christopher Wedlake; Anis Ahmad; Terry M. Peters

doi:10.1117/12.773178

17 March 2008 Object identification accuracy under ultrasound enhanced virtual reality for minimally invasive cardiac surgery

Andrew D. Wiles, John Moore, Cristian A. Linte, Christopher Wedlake, Anis Ahmad, Terry M. Peters

Author Affiliations +

Proceedings Volume 6918, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling; 69180E (2008) https://doi.org/10.1117/12.773178
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

A 2D ultrasound enhanced virtual reality surgical guidance system has been under development for some time in our lab. The new surgical guidance platform has been shown to be effective in both the laboratory and clinical settings, however, the accuracy of the tracked 2D ultrasound has not been investigated in detail in terms of the applications for which we intend to use it (i.e., mitral valve replacement and atrial septal defect closure). This work focuses on the development of an accuracy assessment protocol specific to the assessment of the calibration methods used to determine the rigid transformation between the ultrasound image and the tracked sensor. Specifically, we test a Z-bar phantom calibration method and a phantomless calibration method and compared the accuracy of tracking ultrasound images from neuro, transesophageal, intracardiac and laparoscopic ultrasound transducers. This work provides a fundamental quantitative description of the image-guided accuracy that can be obtained with this new surgical guidance system.

Citation Download Citation

Andrew D. Wiles, John Moore, Cristian A. Linte, Christopher Wedlake, Anis Ahmad, and Terry M. Peters "Object identification accuracy under ultrasound enhanced virtual reality for minimally invasive cardiac surgery", Proc. SPIE 6918, Medical Imaging 2008: Visualization, Image-Guided Procedures, and Modeling, 69180E (17 March 2008); https://doi.org/10.1117/12.773178

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