Fast noniterative calibration of an external motion tracking device

Prospective motion correction of magnetic resonance (MR) scans commonly uses an external device, such as a camera, to track the pose of the organ of interest. However, in order for external tracking data to be translated into the MR scanner reference frame, the pose of the camera relative to the MR scanner must be known accurately. Here, we describe a fast, accurate, non‐iterative technique to determine the position of an external tracking device de novo relative to the MR reference frame.

[1]  K. S. Arun,et al.  Least-Squares Fitting of Two 3-D Point Sets , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Ching-Cheng Wang,et al.  Extrinsic calibration of a vision sensor mounted on a robot , 1992, IEEE Trans. Robotics Autom..

[3]  Timothy A. Clarke,et al.  Comparison of some techniques for the subpixel location of discrete target images , 1994, Other Conferences.

[4]  Tolga Çukur,et al.  Hybrid prospective and retrospective head motion correction to mitigate cross‐calibration errors , 2012, Magnetic resonance in medicine.

[5]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[6]  Fenghua Jin,et al.  Prospective head‐movement correction for high‐resolution MRI using an in‐bore optical tracking system , 2009, Magnetic resonance in medicine.

[7]  Richard A. Volz,et al.  Estimating 3-D location parameters using dual number quaternions , 1991, CVGIP Image Underst..

[8]  Sascha Krueger,et al.  Prospective real‐time correction for arbitrary head motion using active markers , 2009, Magnetic resonance in medicine.

[9]  Joachim Hornegger,et al.  Real‐time optical motion correction for diffusion tensor imaging , 2011, Magnetic resonance in medicine.

[10]  P. Schönemann,et al.  A generalized solution of the orthogonal procrustes problem , 1966 .

[11]  Oliver Speck,et al.  Measurement and Correction of Microscopic Head Motion during Magnetic Resonance Imaging of the Brain , 2012, PloS one.

[12]  Jordan Muraskin,et al.  Echo‐planar imaging with prospective slice‐by‐slice motion correction using active markers , 2011, Magnetic resonance in medicine.

[13]  S Thesen,et al.  Prospective acquisition correction for head motion with image‐based tracking for real‐time fMRI , 2000, Magnetic resonance in medicine.

[14]  Oliver Speck,et al.  Magnetic resonance imaging of freely moving objects: prospective real-time motion correction using an external optical motion tracking system , 2006, NeuroImage.

[15]  Robert B. Fisher,et al.  Estimating 3-D rigid body transformations: a comparison of four major algorithms , 1997, Machine Vision and Applications.

[16]  Maxim Zaitsev,et al.  An embedded optical tracking system for motion-corrected magnetic resonance imaging at 7T , 2012, Magnetic Resonance Materials in Physics, Biology and Medicine.

[17]  Berthold K. P. Horn,et al.  Closed-form solution of absolute orientation using unit quaternions , 1987 .

[18]  Kostas Daniilidis,et al.  Hand-Eye Calibration Using Dual Quaternions , 1999, Int. J. Robotics Res..

[19]  Oliver Speck,et al.  Prospective motion correction in brain imaging: A review , 2013, Magnetic resonance in medicine.