@article {Lugez2016a,
	title = {Enhanced electromagnetic catheter tracking with application in high-dose-rate brachytherapy},
	year = {2016},
	author = {Elodie Lugez and Hossein Sadjadi and C.P. Joshi and Selim G. Akl and Gabor Fichtinger}
}
@conference {Lugez2015,
	title = {Nonholonomic catheter path reconstruction using electromagnetic tracking},
	booktitle = {SPIE Medical Imaging 2015},
	volume = {9415},
	year = {2015},
	pages = {94150L-94150L-7},
	abstract = {<p>Catheter path reconstruction is a necessary step in many clinical procedures, such as cardiovascular interventions and high-dose-rate brachytherapy. To overcome limitations of standard imaging modalities, electromagnetic tracking has been employed to reconstruct catheter paths. However, tracking errors pose a challenge in accurate path reconstructions. We address this challenge by means of a filtering technique incorporating the electromagnetic measurements with the nonholonomic motion constraints of the sensor inside a catheter. The nonholonomic motion model of the sensor within the catheter and the electromagnetic measurement data were integrated using an extended Kalman filter. The performance of our proposed approach was experimentally evaluated using the Ascension{\^a}{\texteuro}{\texttrademark}s 3D Guidance trakStar electromagnetic tracker. Sensor measurements were recorded during insertions of an electromagnetic sensor (model 55) along ten predefined ground truth paths. Our method was implemented in MATLAB and applied to the measurement data. Our reconstruction results were compared to raw measurements as well as filtered measurements provided by the manufacturer. The mean of the root-mean-square (RMS) errors along the ten paths was 3.7 mm for the raw measurements, and 3.3 mm with manufacturer{\^a}{\texteuro}{\texttrademark}s filters. Our approach effectively reduced the mean RMS error to 2.7 mm. Compared to other filtering methods, our approach successfully improved the path reconstruction accuracy by exploiting the sensor{\^a}{\texteuro}{\texttrademark}s nonholonomic motion constraints in its formulation. Our approach seems promising for a variety of clinical procedures involving reconstruction of a catheter path.</p>
},
	doi = {10.1117/12.2081561},
	url = {http://dx.doi.org/10.1117/12.2081561},
	author = {Elodie Lugez and Hossein Sadjadi and Selim G. Akl and Gabor Fichtinger}
}
@article {Sadjadi2015b,
	title = {Simultaneous electromagnetic tracking and calibration for dynamic field distortion compensation},
	journal = {IEEE Transactions on Biomedical Engineering (TBME)},
	year = {2015},
	month = {11/2015},
	doi = {10.1109/TBME.2015.2502138},
	author = {Hossein Sadjadi and Keyvan Hashtrudi-Zaad and Gabor Fichtinger}
}
@article {Sadjadi2015a,
	title = {Simultaneous Localization and Calibration for Electromagnetic Tracking Systems},
	journal = {The International Journal of Medical Robotics and Computer Assisted Surgery (IJMRCAS)},
	year = {2015},
	doi = {10.1002/rcs},
	author = {Hossein Sadjadi and Keyvan Hashtrudi-Zaad and Gabor Fichtinger}
}
@article {Sadjadi2014a,
	title = {Development and Evaluation of a Needle Deflection Estimation Method},
	year = {2014},
	month = {03/2014},
	author = {Hossein Sadjadi and Keyvan Hashtrudi-Zaad and Gabor Fichtinger}
}
@mastersthesis {Sadjadi2014d,
	title = {Electromagnetic instrument tracking in computer-assisted interventions},
	volume = {PhD},
	year = {2014},
	month = {08/2014},
	school = {Queen{\textquoteright}s University},
	address = {Kingston, ON},
	url = {http://qspace.library.queensu.ca/handle/1974/12358},
	author = {Hossein Sadjadi}
}
@article {Lugez2014b,
	title = {Electromagnetic Tracking for Catheter Path Reconstruction},
	year = {2014},
	month = {09/2014},
	pages = {43},
	address = {Massachusetts Institute of Technology, Boston, USA},
	author = {Elodie Lugez and Hossein Sadjadi and Selim G. Akl and Gabor Fichtinger}
}
@article {Lugez2014a,
	title = {Electromagnetic tracking in surgical and interventional environments: usability study},
	journal = {Int J CARS},
	year = {2014},
	month = {09/2014},
	author = {Elodie Lugez and Hossein Sadjadi and David R Pichora and Randy Ellis and Selim G. Akl and Gabor Fichtinger}
}
@conference {Sadjadi2014c,
	title = {Electromagnetic tracking performance analysis and optimization},
	booktitle = {International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)},
	year = {2014},
	month = {09/2014},
	author = {Yu Qi and Hossein Sadjadi and Yeo, Caitlin T and Keyvan Hashtrudi-Zaad and Gabor Fichtinger}
}
@article {Sadjadi2014b,
	title = {Needle Deflection Estimation: Prostate Brachytherapy Phantom Experiments},
	journal = {International Journal of Computer Assisted Radiology and Surgery (IJCARS)},
	year = {2014},
	month = {03/2014},
	doi = {10.1007/s11548-014-0985-0},
	url = {http://dx.doi.org/10.1007/s11548-014-0985-0},
	author = {Hossein Sadjadi and Keyvan Hashtrudi-Zaad and Gabor Fichtinger}
}
@conference {Sadjadi2013b,
	title = {Experimental evaluation of needle deflection estimation for brachytherapy},
	booktitle = {Computer Assisted Radiology and Surgery (CARS 2013)},
	year = {2013},
	month = {03/2013},
	author = {Hossein Sadjadi and Keyvan Hashtrudi-Zaad and Xu, Helen and Gabor Fichtinger}
}
@article {Sadjadi2013a,
	title = {Fusion of Electromagnetic Trackers to Improve Needle Deflection Estimation: Simulation Study},
	journal = {IEEE Transactions on Biomedical Engineering},
	volume = {60},
	year = {2013},
	month = {10/2013},
	pages = {2706 - 2715},
	issn = {0018-9294},
	doi = {10.1109/TBME.2013.2262658},
	author = {Hossein Sadjadi and Keyvan Hashtrudi-Zaad and Gabor Fichtinger}
}
@conference {Sadjadi2012,
	title = {Needle Deflection Estimation using Fusion of Electromagnetic Trackers},
	booktitle = {34th Annual International Conference of the IEEE EMBS (EMBC 2012)},
	year = {2012},
	month = {08/28/2012},
	pages = {952-955},
	address = {San Diego, California USA},
	abstract = {<p>We present a needle deflection estimation method to compensate for needle bending during insertion into deformable tissue. We combine a kinematic needle deflection estimation model, electromagnetic (EM) trackers, and a Kalman filter (KF). We reduce the impact of error from the needle deflection estimation model by using the fusion of two EM trackers to report the approximate needle tip position in real-time. One reliable EM tracker is installed on the needle base, and estimates the needle tip position using the kinematic needle deflection model. A smaller but much less reliable EM tracker is installed on the needle tip, and estimates the needle tip position through direct noisy measurements. Using a KF, the sensory information from both EM trackers is fused to provide a reliable estimate of the needle tip position with much reduced variance in the estimation error. We then implement this method to compensate for needle deflection during simulated prostate cancer brachytherapy needle insertion. At a typical maximum insertion depth of 15 cm, needle tip mean estimation error was reduced from 2.39 mm to 0.31 mm, which demonstrates the effectiveness of our method, offering a clinically practical solution.</p>
},
	author = {Hossein Sadjadi and Keyvan Hashtrudi-Zaad and Gabor Fichtinger}
}
