TY - GEN
T1 - Active echo
T2 - 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014
AU - Guo, Xiaoyu
AU - Cheng, Alexis
AU - Zhang, Haichong K.
AU - Kang, Hyun Jae
AU - Etienne-Cummings, Ralph
AU - Boctor, Emad M.
PY - 2014/1/1
Y1 - 2014/1/1
N2 - In ultrasound-guided medical procedures, accurate tracking of interventional tools with respect to the US probe is crucial to patient safety and clinical outcome. US probe tracking requires an unavoidable calibration procedure to recover the rigid body transformation between the US image and the tracking coordinate system. In literature, almost all calibration methods have been performed on passive phantoms. There are several challenges to these calibration methods including dependency on ultrasound image quality and parameters such as frequency, depth, and beam-thickness. In this work, for the first time we introduce an active echo (AE) phantom for US calibration. The phantom actively detects and responds to the US beams from the imaging probe. This active approach allows reliable and accurate identification of the ultrasound image mid-plane independent of the image quality. It also enables automatic point segmentations. Both the target localization and segmentation can be done automatically, so the user dependency is minimized. The AE phantom is compared with a gold standard crosswire (CW) phantom in a robotic US experimental setup. The result indicates that AE calibration phantom provides a localization precision of 223 μm, and an overall reconstruction error of 850 μm. Auto-segmentation is also tested and proved to have the similar performance as the manual segmentation.
AB - In ultrasound-guided medical procedures, accurate tracking of interventional tools with respect to the US probe is crucial to patient safety and clinical outcome. US probe tracking requires an unavoidable calibration procedure to recover the rigid body transformation between the US image and the tracking coordinate system. In literature, almost all calibration methods have been performed on passive phantoms. There are several challenges to these calibration methods including dependency on ultrasound image quality and parameters such as frequency, depth, and beam-thickness. In this work, for the first time we introduce an active echo (AE) phantom for US calibration. The phantom actively detects and responds to the US beams from the imaging probe. This active approach allows reliable and accurate identification of the ultrasound image mid-plane independent of the image quality. It also enables automatic point segmentations. Both the target localization and segmentation can be done automatically, so the user dependency is minimized. The AE phantom is compared with a gold standard crosswire (CW) phantom in a robotic US experimental setup. The result indicates that AE calibration phantom provides a localization precision of 223 μm, and an overall reconstruction error of 850 μm. Auto-segmentation is also tested and proved to have the similar performance as the manual segmentation.
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U2 - 10.1007/978-3-319-10470-6_50
DO - 10.1007/978-3-319-10470-6_50
M3 - Conference contribution
AN - SCOPUS:84906981315
SN - 9783319104690
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 397
EP - 404
BT - Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings
PB - Springer Verlag
Y2 - 14 September 2014 through 18 September 2014
ER -