Ultrasound probe localization by tracking skin features
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Brian W. Anthony and Charles G. Sodini.
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Ultrasound probe localization with respect to the human body is essential for freehand three-dimensional ultrasound (3D US), image-guided surgery, and longitudinal studies. Existing methods for probe localization, however, typically involve bulky and expensive equipment, and suffer from patient motion artifacts. This thesis presents a highly cost-effective and miniature-mobile system for ultrasound probe localization in six degrees of freedom that is robust to rigid patient motion. In this system, along with each acquisition of an ultrasound image, skin features in the scan region are recorded by a lightweight camera rigidly mounted to the probe. Through visual simultaneous localization and mapping (visual SLAM), a skin map is built based on skin features and the probe poses are estimated. Each pose estimate is refined in a Bayesian probabilistic framework that incorporates visual SLAM, ultrasound images, and a prior motion model. Extraction of human skin features and their distinctiveness in the context of probe relocalization were extensively evaluated. The system performance for free-hand 3D US was validated on three body parts: lower leg, abdomen, and neck. The motion errors were quantified, and the volume reconstructions were validated through comparison with ultrasound images. The reconstructed tissue structures were shown to be consistent with observations in ultrasound imaging, which suggests the system's potential in improving clinical workflows. In conjunction with this localization system, an intuitive interface was developed to provide real-time visual guidance for ultrasound probe realignment, which allows repeatable image acquisition in localized therapies and longitudinal studies. Through in-vivo experiments, it was shown that this system significantly improves spatial consistency of tissue structures in repeated ultrasound scans.
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.Cataloged from PDF version of thesis.Includes bibliographical references (pages 131-141).
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology
Electrical Engineering and Computer Science.