@inbook{cc9b61d4090f4101b6e1a1094822646d,
title = "Similarity registration problems for 2D/3D ultrasound calibration",
abstract = "We propose a minimal solution for the similarity registration (rigid pose and scale) between two sets of 3D lines, and also between a set of co-planar points and a set of 3D lines. The first problem is solved up to 8 discrete solutions with a minimum of 2 line-line correspondences, while the second is solved up to 4 discrete solutions using 4 point-line correspondences. We use these algorithms to perform the extrinsic calibration between a pose tracking sensor and a 2D/3D ultrasound (US) curvilinear probe using a tracked needle as calibration target. The needle is tracked as a 3D line, and is scanned by the ultrasound as either a 3D line (3D US) or as a 2D point (2D US). Since the scale factor that converts US scan units to metric coordinates is unknown, the calibration is formulated as a similarity registration problem. We present results with both synthetic and real data and show that the minimum solutions outperform the correspondent non-minimal linear formulations.",
keywords = "Calibration, Medical imaging, Similarity registration, Ultrasound",
author = "Francisco Vasconcelos and Donald Peebles and Sebastien Ourselin and Danail Stoyanov",
year = "2016",
month = sep,
day = "17",
doi = "10.1007/978-3-319-46466-4\_11",
language = "English",
isbn = "9783319464657",
volume = "9910 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "171--187",
booktitle = "Computer Vision - 14th European Conference, ECCV 2016, Proceedings",
address = "Germany",
}