Vinyas Harish
Undergraduate Student
School of Computing
Queen's University
During his time at The Perk Lab, Vinyas worked on a variety of projects in the ultrasound-guided intervention space. Vinyas co-designed a system for the measurement and evaluation of electromagnetic tracking error in computer-assisted interventions, with a particular focus on navigated breast-conserving surgery. In addition, he co-designed a low-cost training phantom for pericardiocentesis, aided in multiple training studies at the Queen's Clinical Simulation Centre, and supervised two high school student interns. Vinyas graduated from the Biomedical Computing program in 2017 and now continues his studies in the joint MD/PhD program at the University of Toronto
House, Rachael; Lasso, Andras; Harish, Vinyas; Baum, Zachary M C; Fichtinger, Gabor
SPIE Medical Imaging, 2017.
@conference{House2017,
title = {Evaluation of the Intel RealSense SR300 camera for image-guided interventions and application in vertebral level localization},
author = {Rachael House and Andras Lasso and Vinyas Harish and Zachary M C Baum and Gabor Fichtinger},
url = {https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/House2017a.pdf},
year = {2017},
date = {2017-01-01},
urldate = {2017-01-01},
booktitle = {SPIE Medical Imaging},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Harish, Vinyas; Bibic, Eden; Lasso, Andras; Holden, M.; Vaughan, Thomas; Baum, Zachary M C; Ungi, Tamas; Fichtinger, Gabor
Monitoring electromagnetic tracking error using redundant sensors Conference
SPIE Medical Imaging 2017, SPIE Society for Optics and Photonics SPIE Society for Optics and Photonics, Orlando, FL, USA, 2017.
@conference{Harish2017a,
title = {Monitoring electromagnetic tracking error using redundant sensors},
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},
url = {https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Harish2017a.pdf},
year = {2017},
date = {2017-01-01},
urldate = {2017-01-01},
booktitle = {SPIE Medical Imaging 2017},
publisher = {SPIE Society for Optics and Photonics},
address = {Orlando, FL, USA},
organization = {SPIE Society for Optics and Photonics},
abstract = {<div class="page" title="Page 1"> <div class="layoutArea"> <div class="column"> <p><span style="font-family:trebuchet ms,helvetica,sans-serif"><span style="font-size:12px"><strong>PURPOSE: </strong>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. <strong>METHODS: </strong>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. <strong>RESULTS: </strong>Measuring the deviation in the reported inter-sensor distance and </span></span><span style="font-family:timesnewromanpsmt; font-size:10.000000pt"><span style="font-family:lucida sans unicode,lucida grande,sans-serif"><span style="font-size:10px"><span style="font-size:12px"><span style="font-family:arial,helvetica,sans-serif"><span style="font-family:trebuchet ms,helvetica,sans-serif">angle</span></span></span></span></span></span><span style="font-family:trebuchet ms,helvetica,sans-serif"><span style="font-size:12px"> 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%. <strong>CONCLUSION: </strong>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 </span></span><span style="font-family:timesnewromanpsmt; font-size:10.000000pt"><span style="font-family:lucida sans unicode,lucida grande,sans-serif"><span style="font-size:10px"><span style="font-size:12px"><span style="font-family:arial,helvetica,sans-serif"><span style="font-family:trebuchet ms,helvetica,sans-serif">machine,</span></span></span></span></span></span><span style="font-family:trebuchet ms,helvetica,sans-serif"><span style="font-size:12px"> and improve the sensitivity of our method before application in real procedures. </span></span></p>
</div>
</div>
</div>},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
<div class="page" title="Page 1"> <div class="layoutArea"> <div class="column"> <p><span style="font-family:trebuchet ms,helvetica,sans-serif"><span style="font-size:12px"><strong>PURPOSE: </strong>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. <strong>METHODS: </strong>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. <strong>RESULTS: </strong>Measuring the deviation in the reported inter-sensor distance and </span></span><span style="font-family:timesnewromanpsmt; font-size:10.000000pt"><span style="font-family:lucida sans unicode,lucida grande,sans-serif"><span style="font-size:10px"><span style="font-size:12px"><span style="font-family:arial,helvetica,sans-serif"><span style="font-family:trebuchet ms,helvetica,sans-serif">angle</span></span></span></span></span></span><span style="font-family:trebuchet ms,helvetica,sans-serif"><span style="font-size:12px"> 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%. <strong>CONCLUSION: </strong>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 </span></span><span style="font-family:timesnewromanpsmt; font-size:10.000000pt"><span style="font-family:lucida sans unicode,lucida grande,sans-serif"><span style="font-size:10px"><span style="font-size:12px"><span style="font-family:arial,helvetica,sans-serif"><span style="font-family:trebuchet ms,helvetica,sans-serif">machine,</span></span></span></span></span></span><span style="font-family:trebuchet ms,helvetica,sans-serif"><span style="font-size:12px"> and improve the sensitivity of our method before application in real procedures. </span></span></p>
</div>
</div>
</div>
</div>
</div>
</div>
Lia, H.; Keri, Zsuzsanna; Holden, M.; Harish, Vinyas; Mitchell, Christopher H; Ungi, Tamas; Fichtinger, Gabor
Training with Perk Tutor improves ultrasound-guided in-plane needle insertion skill Conference
SPIE Medical Imaging, vol. 10135, Orlando, FL, 2017.
@conference{Lia2017,
title = {Training with Perk Tutor improves ultrasound-guided in-plane needle insertion skill},
author = {H. Lia and Zsuzsanna Keri and M. Holden and Vinyas Harish and Christopher H Mitchell and Tamas Ungi and Gabor Fichtinger},
url = {https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Lia-SPIE2017.pdf},
year = {2017},
date = {2017-01-01},
urldate = {2017-01-01},
booktitle = {SPIE Medical Imaging},
volume = {10135},
address = {Orlando, FL},
abstract = {<p><strong>PURPOSE: </strong>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. </p>
<p><strong>METHODS: </strong>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. </p> <p><strong>RESULTS: </strong>The needle tracking measurements showed, for the Perk Tutor group, lower average distance between the needle tip and ultrasound (1.2 [0.9 – 2.8] mm \emph{vs }2.7 [2.3 – 4.0] mm, respectively; \emph{P }= 0.023) and lower maximum distance between the needle tip and ultrasound (2.2 [1.9 – 3.2] mm \emph{vs }4.6 [3.9 – 6.2] mm, respectively; \emph{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. </p>
<p><strong>CONCLUSION: </strong>The Perk Tutor group had significantly reduced distance from the needle tip to the ultrasound plane. Training with Perk Tutor can improve trainees’ needle and ultrasound coordination. </p>},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
<p><strong>PURPOSE: </strong>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. </p>
<p><strong>METHODS: </strong>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. </p> <p><strong>RESULTS: </strong>The needle tracking measurements showed, for the Perk Tutor group, lower average distance between the needle tip and ultrasound (1.2 [0.9 – 2.8] mm vs 2.7 [2.3 – 4.0] mm, respectively; P = 0.023) and lower maximum distance between the needle tip and ultrasound (2.2 [1.9 – 3.2] mm vs 4.6 [3.9 – 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. </p>
<p><strong>CONCLUSION: </strong>The Perk Tutor group had significantly reduced distance from the needle tip to the ultrasound plane. Training with Perk Tutor can improve trainees’ needle and ultrasound coordination. </p>
<p><strong>METHODS: </strong>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. </p> <p><strong>RESULTS: </strong>The needle tracking measurements showed, for the Perk Tutor group, lower average distance between the needle tip and ultrasound (1.2 [0.9 – 2.8] mm vs 2.7 [2.3 – 4.0] mm, respectively; P = 0.023) and lower maximum distance between the needle tip and ultrasound (2.2 [1.9 – 3.2] mm vs 4.6 [3.9 – 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. </p>
<p><strong>CONCLUSION: </strong>The Perk Tutor group had significantly reduced distance from the needle tip to the ultrasound plane. Training with Perk Tutor can improve trainees’ needle and ultrasound coordination. </p>
Harish, Vinyas; Bibic, Eden; Lasso, Andras; Holden, M.; Vaughan, Thomas; Baum, Zachary M C; Ungi, Tamas; Fichtinger, Gabor
An application of redundant sensors for intraoperative electromagnetic tracking error monitoring Conference
15th Annual Imaging Network Ontario Symposium, London, ON, Canada, 2017.
@conference{Harish2017b,
title = {An application of redundant sensors for intraoperative electromagnetic tracking error monitoring},
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},
url = {https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Harish2017b.pdf},
year = {2017},
date = {2017-01-01},
urldate = {2017-01-01},
booktitle = {15th Annual Imaging Network Ontario Symposium},
address = {London, ON, Canada},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Bibic, Eden; Baum, Zachary M C; Harish, Vinyas; Ungi, Tamas; Lasso, Andras; Fichtinger, Gabor
PLUS Model Catalog: A library of 3D-printable models Conference
15th Annual Imaging Network Ontario Symposiuim, Imaging Network Ontario (ImNO), London, Canada, 2017.
@conference{Bibic2017a,
title = {PLUS Model Catalog: A library of 3D-printable models},
author = {Eden Bibic and Zachary M C Baum and Vinyas Harish and Tamas Ungi and Andras Lasso and Gabor Fichtinger},
url = {https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Bibic2017a-Poster.pptx
https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Bibic2017a-Poster.pptx},
year = {2017},
date = {2017-01-01},
urldate = {2017-01-01},
booktitle = {15th Annual Imaging Network Ontario Symposiuim},
publisher = {Imaging Network Ontario (ImNO)},
address = {London, Canada},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Harish, Vinyas; Baksh, A; Ungi, Tamas; Lasso, Andras; Baum, Zachary M C; Gauvin, G; Engel, C. Jay; Rudan, John; Fichtinger, Gabor
Measurement of electromagnetic tracking error in a navigated breast surgery setup Conference
SPIE Medical Imaging 2016, vol. 9786, SPIE Medical Imaging SPIE Medical Imaging, San Diego, CA, United States, Feb. 29, 2016, 2016.
@conference{Harish2016a,
title = {Measurement of electromagnetic tracking error in a navigated breast surgery setup},
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},
url = {https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Harish2016a.pdf},
year = {2016},
date = {2016-01-01},
urldate = {2016-01-01},
booktitle = {SPIE Medical Imaging 2016},
volume = {9786},
publisher = {SPIE Medical Imaging},
address = {San Diego, CA, United States, Feb. 29, 2016},
organization = {SPIE Medical Imaging},
abstract = {<p>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°. 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.</p>},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
<p>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°. 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.</p>
Baksh, A; Harish, Vinyas; Ungi, Tamas; Pal, R; Fichtinger, Gabor
An inexpensive system for competency-based pericardiocentesis training Conference
14th Annual Imaging Network Ontario Symposium (ImNO), Imaging Network Ontario (ImNO), Toronto, Canada, 2016.
@conference{Baksh2016a,
title = {An inexpensive system for competency-based pericardiocentesis training},
author = {A Baksh and Vinyas Harish and Tamas Ungi and R Pal and Gabor Fichtinger},
url = {https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Baksh2016a.pdf},
year = {2016},
date = {2016-01-01},
urldate = {2016-01-01},
booktitle = {14th Annual Imaging Network Ontario Symposium (ImNO)},
publisher = {Imaging Network Ontario (ImNO)},
address = {Toronto, Canada},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Harish, Vinyas; Baksh, A; Ungi, Tamas; Pal, R; Fichtinger, Gabor
A low-cost system for image-guided computer-navigated pericardiocentesis training Conference
30th International Congress & Exhibition on Computer Assisted Radiology and Surgery (CARS), vol. Int J CARS (2016) 11 (Suppl 1), CARS, Heidelberg, Germany, 2016.
@conference{Harish2016b,
title = {A low-cost system for image-guided computer-navigated pericardiocentesis training},
author = {Vinyas Harish and A Baksh and Tamas Ungi and R Pal and Gabor Fichtinger},
url = {https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Harish2016b.pdf},
year = {2016},
date = {2016-01-01},
urldate = {2016-01-01},
booktitle = {30th International Congress & Exhibition on Computer Assisted Radiology and Surgery (CARS)},
volume = {Int J CARS (2016) 11 (Suppl 1)},
pages = {S112},
publisher = {CARS},
address = {Heidelberg, Germany},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Harish, Vinyas; Baksh, A; Ungi, Tamas; Lasso, Andras; Baum, Zachary M C; Gauvin, G; Engel, C. Jay; Rudan, John; Fichtinger, Gabor
Monitoring electromagnetic tracking error in computer-navigated breast cancer surgery Conference
14th Annual Imaging Network Ontario Symposium (ImNO), Imaging Network Ontario (ImNO), Toronto, Canada, 2016.
@conference{Harish2016c,
title = {Monitoring electromagnetic tracking error in computer-navigated breast cancer surgery},
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},
url = {https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Harish2016c.pdf},
year = {2016},
date = {2016-01-01},
urldate = {2016-01-01},
booktitle = {14th Annual Imaging Network Ontario Symposium (ImNO)},
publisher = {Imaging Network Ontario (ImNO)},
address = {Toronto, Canada},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Harish, Vinyas; Ungi, Tamas; Lasso, Andras; MacDonald, Andrew; Nanji, Sulaiman; Fichtinger, Gabor
Intraoperative visualization and assessment of electromagnetic tracking error Conference
SPIE Medical Imaging 2015, vol. 9415, Orlando,FL, United States, Feb. 23, 2015, 2015.
@conference{Harish2015,
title = {Intraoperative visualization and assessment of electromagnetic tracking error},
author = {Vinyas Harish and Tamas Ungi and Andras Lasso and Andrew MacDonald and Sulaiman Nanji and Gabor Fichtinger},
url = {http://dx.doi.org/10.1117/12.2082330
https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Harish2015-manuscript.pdf
https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/02/Harish2015-poster.pdf},
doi = {10.1117/12.2082330},
year = {2015},
date = {2015-01-01},
urldate = {2015-01-01},
booktitle = {SPIE Medical Imaging 2015},
volume = {9415},
pages = {94152H-94152H-6},
address = {Orlando,FL, United States, Feb. 23, 2015},
abstract = {<p>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.</p>},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
<p>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.</p>