Publications

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Barr, C., Hisey R., Ungi T., & Fichtinger G. (2021).  Ultrasound Probe Pose Classification for Task Recognition in Central Venous Catheterization. Imaging Network of Ontario Symposium. PDF icon CBarr2021a.pdf (391.8 KB)
Barr, C., Hisey R., Ungi T., & Fichtinger G. (2021).  Ultrasound Probe Pose Classification for Task Recognition in Central Venous Catheterization. 43rd Conference of the IEEE Engineering Medicine and Biology Society.
Ungi, T., Moult E., Schwab J. H., & Fichtinger G. (2013).  Ultrasound Snapshots in Percutaneous Pedicle Screw Placement Navigation: A Feasibility Study. Clinical Orthopaedics and Related Research. PDF icon Ungi2013e_WebVersion.pdf (653.91 KB)
Baum, Z. M. C., Ungi T., Lasso A., Church B., Schlenger C., & Fichtinger G. (2018).  Ultrasound-based vertebral landmark localization using deformable spine models. 16th Annual Imaging Network Ontario Symposiuim. PDF icon Baum2018b.pdf (1.03 MB)PDF icon Baum2018b-Poster.pdf (961.09 KB)
Moult, E., Ungi T., Welch M., Lu J., McGraw R. C., & Fichtinger G. (2013).  Ultrasound-guided facet joint injection training using Perk Tutor. International Journal of Computer Assisted Radiology and Surgery. 8, 831-6.
Ungi, T., Lasso A., Welch M., Jalal R., Nagpal S., Jaeger M., et al. (2012).  Ultrasound-guided spinal needle placement on open source platform. ImNO2012 - Imaging Network Ontario Symposium. PDF icon Ungi2012a.pdf (267.8 KB)
Baum, Z. M. C., Ungi T., Lasso A., & Fichtinger G. (2017).  Usability of a real-time tracked augmented reality display system in musculoskeletal injections. SPIE Medical Imaging 2017: Image-Guided Procedures, Robotic Interventions, and Modeling. PDF icon Baum2017a.pdf (889.77 KB)
Wu, V., Ungi T., & Fichtinger G. (2019).  Using Deep Learning for Transverse Process Detection in Spinal Ultrasounds. 17th Annual Imaging Network Ontario Symposium (ImNO). PDF icon Wu2019a.pdf (158.09 KB)
Wu, V., Ungi T., Sunderland K. R., Pigeau G., Schonewille A., & Fichtinger G. (2020).  Using multiple frame U-net for automated segmentation of spinal ultrasound images. 18th Annual Imaging Network Ontario (ImNO) Symposium. PDF icon Wu2020b.pdf (133.02 KB)
Yeo, C. T., MacDonald A., Ungi T., Lasso A., Jalink D., Zevin B., et al. (2018).  Utility of 3D Reconstruction of 2D Liver Computed Tomography/Magnetic Resonance Images as a Surgical Planning Tool for Residents in Liver Resection Surgery. Journal of Surgical Education. 75, 792-797.PDF icon Yeo2017.pdf (527.68 KB)
Isen, J., Hisey R., Ungi T., & Fichtinger G. (2019).  Utilizing a convolutional neural network for tool detection in central venous catheterization. 33rd International Congress & Exhibition on Computer Assisted Radiology and Surgery (CARS). PDF icon Isen2019b.pdf (129.5 KB)
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Yan, C., Tabanfar R., Kempston M., Borschneck D., Ungi T., & Fichtinger G. (2016).  Vertebral landmark visualization with portable ultrasound imaging in scoliosis monitoring. 14th Annual Imaging Network Ontario Symposium (ImNO). PDF icon Yan2016b.pdf (388.09 KB)
Vaughan, T., Ungi T., Lasso A., Gauvin G., C. Engel J., Rudan J., et al. (2017).  Virtual views controlled by surgical tools for computer assisted interventions. 15th Annual Imaging Network Ontario Symposium (ImNO). PDF icon Vaughan2017a.pdf (366.19 KB)
Baum, Z. M. C., Ungi T., Lasso A., Church B., Schlenger C., & Fichtinger G. (2018).  Visual aid for identifying vertebral landmarks in ultrasound. SPIE Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling. 10576, 105760Z.PDF icon Baum2018a.pdf (1.46 MB)
Carter, K., Lasso A., Ungi T., Morin E., & Fichtinger G. (2015).  Visual feedback mounted on surgical tool. 13th Imaging Network of Ontario Symposium (ImNO 2015). 36.PDF icon Carter2015a.pdf (123.23 KB)File Carter2015a-poster.pptx (3.24 MB)File Carter2015a-slides.pptx (21.62 MB)
Carter, K., Vaughan T., Holden M. S., Gauvin G., Pezeshki P., Lasso A., et al. (2016).  Visual feedback mounted on surgical tool: proof of concept. SPIE Medical Imaging 2016. 9786,
Church, B., Lasso A., Schlenger C., Borschneck D. P., Mousavi P., Fichtinger G., et al. (2017).  Visualization of scoliotic spine using ultrasound-accessible skeletal landmarks. SPIE Medical Imaging 2017. PDF icon Church2017a.pdf (814.95 KB)

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