Publications
Real-time needle tip tracking using Fiber Brag Grating sensors for MRI-guided prostate interventions: Design considerations.
9th Interventional MRI Symposium (IMRI 2012).
Abstract_Esteban_final_6.pdf (91.28 KB)
(2012). 
Reconstruction of Needle Tracts from Fluoroscopy in Prostate Brachytherapy.
22nd International Conference of the Society for Medical Innovation and Technology (SMIT).
Gordon2010a.pdf (38.64 KB)
(2010). 
Rotational Encoding of C-arm Fluoroscope with Tilt Sensing Accelerometer.
Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2010. 424-431.
Grzeda2010.pdf (382.55 KB)
(2010). 
C-arm rotation encoding with accelerometers.
International Journal of Computer Assisted Radiation and Surgery. 5, 385-391.
Grzeda2010a.pdf (511.39 KB)
(2010). 
Surgical and interventional robotics: part III [Tutorial].
IEEE Robotics & Automation Magazine. 15, 84–93.
Hager2008.pdf (2.12 MB)
(2008). 
Compilation of a pathological validation database for ultrasound monitoring of tumour ablation.
22nd International Conference of the Society for Medical Innovation and Technology (SMIT).
Hall2010a.pdf (26.04 KB)
(2010). 
Measurement of electromagnetic tracking error in a navigated breast surgery setup.
SPIE Medical Imaging 2016. 9786,
Harish2016a.pdf (4.07 MB)
(2016). 
Monitoring electromagnetic tracking error using redundant sensors.
SPIE Medical Imaging 2017.
Harish2017a.pdf (657.31 KB)
(2017). 
Intraoperative visualization and assessment of electromagnetic tracking error.
SPIE Medical Imaging 2015. 9415, 94152H-94152H-6.
Harish2015-manuscript.pdf (5.7 MB)
Harish2015-poster.pdf (897.74 KB)
(2015). 

Monitoring electromagnetic tracking error in computer-navigated breast cancer surgery.
14th Annual Imaging Network Ontario Symposium (ImNO).
Harish2016c.pdf (1.25 MB)
(2016). 
An application of redundant sensors for intraoperative electromagnetic tracking error monitoring.
15th Annual Imaging Network Ontario Symposium.
Harish2017b.pdf (504.36 KB)
(2017). 
A low-cost system for image-guided computer-navigated pericardiocentesis training.
30th International Congress & Exhibition on Computer Assisted Radiology and Surgery (CARS). Int J CARS (2016) 11 (Suppl 1), S112.
Harish2016b.pdf (959.69 KB)
(2016). 
Accuracy of lesion boundary tracking in navigated breast tumor excision.
SPIE Medical Imaging 2016. 9786, 97860Y-1-6.
Heffernan2016-manuscript.pdf (303.45 KB)
(2016). 
Quantification of edematic effects in prostate brachytherapy interventions.
Medical image computing and computer-assisted intervention (MICCAI). 11, 493–500.
Hefny2008.pdf (408.83 KB)
(2008). 
Feasibility of a touch-free user interface for ultrasound snapshot-guided nephrostomy.
SPIE Medical Imaging 2014: Image-Guided Procedures, Robotic Interventions, and Modeling. 9036, 90362F.
Kotwicz2014.pdf (330.8 KB)
(2014). 
dcmqi: An Open Source Library for Standardized Communication of Quantitative Image Analysis Results Using DICOM.
Cancer Research. 77, e87–e90.
Herz2017.pdf (459.73 KB)
(2017). 
Quantification of intraventricular blood clot in MR-guided focused ultrasound surgery.
SPIE Medical Imaging 2015. 9415, 94152J-94152J-9.
Hess2014a-manuscript.pdf (4.57 MB)
(2015). 
Quantification of intraventricular blood clot in MR-guided focused ultrasound surgery.
(Looi, T., Lasso A., & Fichtinger G., Ed.).SPIE Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling. 9415, 94152J1-94152J9.
(2015). Central Line Tutor: using computer vision workflow recognition in a central venous catheterization training system.
Imaging Network of Ontario Symposium.
RHisey_ImNO2021.pdf (190.87 KB)
(2021). 
System for central venous catheterization training using computer vision-based workflow feedback.
IEEE Transactions on Biomedical Engineering.
(2021). Recognizing workflow tasks in central venous catheterization using convolutional neural networks and reinforcement learning.
International Conference on Computer Assisted Radiology and Surgery. 94-95.
RHisey_CARS_2020.pdf (152.24 KB)
(2020). 
Assessment of the use of webcam based workflow detection for providing real-time feedback in central venous catheterization training.
Imaging Network Ontario (IMNO).
Rebecca_ImNO2018_07.pdf (312.14 KB)
(2018). 
Reinforcement learning approach for video-based task recognition in central venous catheterization.
Imaging Network of Ontario Symposium.
RHisey_ImNO2020.pdf (399.33 KB)
(2020). 
Real-time workflow detection using webcam video for providing real-time feedback in central venous catheterization training.
SPIE Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling.
RHisey_SPIE2018_Full_02.pdf (749.23 KB)
(2018). 
Comparison of convolutional neural networks for central venous catheterization tool detection.
Imaging Network of Ontario Symposium.
RHisey_ImNO2019.pdf (464.16 KB)
(2019). 