@article {Harish2017b, title = {An application of redundant sensors for intraoperative electromagnetic tracking error monitoring}, year = {2017}, address = {London, ON, Canada}, author = {Vinyas Harish and E Bibic and Andras Lasso and M. Holden and Thomas Vaughan and Zachary M C Baum and Tamas Ungi and Gabor Fichtinger} } @conference {House2017, title = {Evaluation of the Intel RealSense SR300 camera for image-guided interventions and application in vertebral level localization}, booktitle = {SPIE Medical Imaging }, year = {2017}, author = {Rachael House and Andras Lasso and Vinyas Harish and Zachary M C Baum and Gabor Fichtinger} } @conference {Harish2017a, title = {Monitoring electromagnetic tracking error using redundant sensors}, booktitle = {SPIE Medical Imaging 2017}, year = {2017}, publisher = {SPIE Society for Optics and Photonics}, organization = {SPIE Society for Optics and Photonics}, address = {Orlando, FL, USA}, abstract = {

PURPOSE: The intraoperative measurement of tracking error is crucial to ensure the reliability of electromagnetically navigated procedures. For intraoperative use, methods need to be quick to set up, easy to interpret, and not interfere with the ongoing procedure. Our goal was to evaluate the feasibility of using redundant electromagnetic sensors to alert users to tracking error in a navigated intervention setup. METHODS: Electromagnetic sensors were fixed to a rigid frame around a region of interest and on surgical tools. A software module was designed to detect tracking error by comparing real-time measurements of the differences between inter-sensor distances and angles to baseline measurements. Once these measurements were collected, a linear support vector machine-based classifier was used to predict tracking errors from redundant sensor readings. RESULTS: Measuring the deviation in the reported inter-sensor distance and angle between the needle and cautery served as a valid indicator for electromagnetic tracking error. The highest classification accuracy, 86\%, was achieved based on readings from the cautery when the two sensors on the cautery were close together. The specificity of this classifier was 93\% and the sensitivity was 82\%. CONCLUSION: Placing redundant electromagnetic sensors in a workspace seems to be feasible for the intraoperative detection of electromagnetic tracking error in controlled environments. Further testing should be performed to optimize the measurement error threshold used for classification in the support vector machine, and improve the sensitivity of our method before application in real procedures.\ 

}, author = {Vinyas Harish and Eden Bibic and Andras Lasso and M. Holden and Thomas Vaughan and Zachary M C Baum and Tamas Ungi and Gabor Fichtinger} } @article {Bibic2017a, title = {PLUS Model Catalog: A library of 3D-printable models}, year = {2017}, publisher = {Imaging Network Ontario (ImNO)}, address = {London, Canada}, author = {Eden Bibic and Zachary M C Baum and Vinyas Harish and Tamas Ungi and Andras Lasso and Gabor Fichtinger} } @conference {Lia2017, title = {Training with Perk Tutor improves ultrasound-guided in-plane needle insertion skill}, booktitle = {SPIE Medical Imaging}, volume = {10135}, year = {2017}, address = {Orlando, FL}, abstract = {

PURPOSE: The open-source Perk Tutor training platform has been shown to improve trainee performance in interventions that require ultrasound guidance. Our goal was to determine if needle coordination of medical trainees can be improved by training with Perk Tutor compared to training with ultrasound only.\ 

METHODS: Twenty participants with no previous experience were randomized into two groups; the Perk Tutor group and the Control group. The Perk Tutor group had access to the 3D visualization while the Control group used ultrasound only during their training. Performance was analyzed, measured and compared by Perk Tutor with regards to four needle coordination metrics. None of the groups had access to 3D visualization during performance testing.\ 

RESULTS: The needle tracking measurements showed, for the Perk Tutor group, lower average distance between the needle tip and ultrasound (1.2 [0.9 {\textendash} 2.8] mm vs 2.7 [2.3 {\textendash} 4.0] mm, respectively; P = 0.023) and lower maximum distance between the needle tip and ultrasound (2.2 [1.9 {\textendash} 3.2] mm vs 4.6 [3.9 {\textendash} 6.2] mm, respectively; P = 0.013). There was no significant difference in average needle to ultrasound plane angle and maximum needle to ultrasound plane distance. All participants were successful in the procedure.\ 

CONCLUSION: The Perk Tutor group had significantly reduced distance from the needle tip to the ultrasound plane. Training with Perk Tutor can improve trainees{\textquoteright} needle and ultrasound coordination.\ 

}, author = {H. Lia and Keri, Zsuzsanna and M. Holden and Vinyas Harish and Mitchell, Christopher H and Tamas Ungi and Gabor Fichtinger} } @article {Baksh2016a, title = {An inexpensive system for competency-based pericardiocentesis training}, year = {2016}, publisher = { Imaging Network Ontario (ImNO)}, address = {Toronto, Canada}, keywords = {Pericardiocentesis, Phantoms}, author = {A Baksh and Vinyas Harish and Tamas Ungi and R Pal and Gabor Fichtinger} } @article {Harish2016b, title = {A low-cost system for image-guided computer-navigated pericardiocentesis training}, volume = {Int J CARS (2016) 11 (Suppl 1)}, year = {2016}, pages = {S112}, publisher = {CARS}, address = {Heidelberg, Germany}, keywords = {Pericardiocentesis, Phantoms}, author = {Vinyas Harish and A Baksh and Tamas Ungi and R Pal and Gabor Fichtinger} } @conference {Harish2016a, title = {Measurement of electromagnetic tracking error in a navigated breast surgery setup}, booktitle = {SPIE Medical Imaging 2016}, volume = {9786}, year = {2016}, publisher = {SPIE Medical Imaging}, organization = {SPIE Medical Imaging}, address = {San Diego, CA, United States, Feb. 29, 2016}, abstract = {

The measurement of tracking error is crucial to ensure the safety and feasibility of electromagnetically tracked, image-guided procedures. Measurement should occur in a clinical environment because electromagnetic field distortion depends on positioning relative to the field generator and metal objects. However, we could not find an accessible and open-source system for calibration, error measurement, and visualization. We developed such a system and tested it in a navigated breast surgery setup.A pointer tool was designed for concurrent electromagnetic and optical tracking. Software modules were developed for automatic calibration of the measurement system, real-time error visualization, and analysis. The system was taken to an operating room to test for field distortion in a navigated breast surgery setup. Positional and rotational electromagnetic tracking errors were then calculated using optical tracking as a ground truth. Our system is quick to set up and can be rapidly deployed. The process from calibration to visualization also only takes a few minutes. Field distortion was measured in the presence of various surgical equipment. Positional and rotational error in a clean field was approximately 0.90 mm and 0.31{\textdegree}. The presence of a surgical table, an electrosurgical cautery, and anesthesia machine increased the error by up to a few tenths of a millimetre and tenth of a degree.In a navigated breast surgery setup, measurement and visualization of tracking error defines a safe working area in the presence of surgical equipment. Our system is available as an extension for the open-source 3D Slicer platform.

}, author = {Vinyas Harish and A Baksh and Tamas Ungi and Andras Lasso and Zachary M C Baum and G Gauvin and C. Jay Engel and John Rudan and Gabor Fichtinger} } @article {Harish2016c, title = {Monitoring electromagnetic tracking error in computer-navigated breast cancer surgery}, year = {2016}, publisher = {Imaging Network Ontario (ImNO)}, address = {Toronto, Canada}, keywords = {Breast cancer, EM Tracking, Lumpectomy}, author = {Vinyas Harish and A Baksh and Tamas Ungi and Andras Lasso and Zachary M C Baum and G Gauvin and C. Jay Engel and John Rudan and Gabor Fichtinger} } @conference {Harish2015, title = {Intraoperative visualization and assessment of electromagnetic tracking error}, booktitle = {SPIE Medical Imaging 2015}, volume = {9415}, year = {2015}, pages = {94152H-94152H-6}, address = {Orlando,FL, United States, Feb. 23, 2015}, abstract = {

Electromagnetic tracking allows for increased flexibility in designing image-guided interventions, however it is well understood that electromagnetic tracking is prone to error. Visualization and assessment of the tracking error should take place in the operating room with minimal interference with the clinical procedure. The goal was to achieve this ideal in an open-source software implementation in a plug and play manner, without requiring programming from the user. We use optical tracking as a ground truth. An electromagnetic sensor and optical markers are mounted onto a stylus device, pivot calibrated for both trackers. Electromagnetic tracking error is defined as difference of tool tip position between electromagnetic and optical readings. Multiple measurements are interpolated into the thin-plate B-spline transform visualized in real time using 3D Slicer. All tracked devices are used in a plug and play manner through the open-source SlicerIGT and PLUS extensions of the 3D Slicer platform. Tracking error was measured multiple times to assess reproducibility of the method, both with and without placing ferromagnetic objects in the workspace. Results from exhaustive grid sampling and freehand sampling were similar, indicating that a quick freehand sampling is sufficient to detect unexpected or excessive field distortion in the operating room. The software is available as a plug-in for the 3D Slicer platforms. Results demonstrate potential for visualizing electromagnetic tracking error in real time for intraoperative environments in feasibility clinical trials in image-guided interventions.

}, doi = {10.1117/12.2082330}, url = {http://dx.doi.org/10.1117/12.2082330}, author = {Vinyas Harish and Tamas Ungi and Andras Lasso and MacDonald, Andrew and Nanji, Sulaiman and Gabor Fichtinger} }