ungi

Name

Tamas Ungi MD, PhD, Associate Director (Clinical Translations)

Short Biography

Tamas Ungi received MD degree in 2006 and PhD degree in Radiology in 2011 from the University of Szeged, Hungary. He is currently an Adjunct Assistant Professor and Senior Research Scientist at the School of Computing and at the Department of Surgery at Queen's University in Canada. He joined the Laboratory for Percutaneous Surgery (Perk Lab) in 2009, where he is the Associate Director of Clinical Translations. His research interests are image-guided medical interventions, and interventional skills education. He is a primary contributor to the SlicerIGT open-source software that facilitates technology development for navigated medical interventions for several academic and industrial projects.

Tamas Ungi's full CV

Affiliation

Institution: Queen's University

Department: School of Computing

Designation: Adjunct faculty

Lab membership period: since 2009

Projects

Publications

2020
Hisey, R., Chen B., Ungi T., Camire D., Erb J., Howes D., et al. (2020). Reinforcement learning approach for video-based task recognition in central venous catheterization. Imaging Network of Ontario Symposium. Google Scholar BibTeX RHisey_ImNO2020.pdf (399.33 KB)
Barr, K., Laframboise J., Ungi T., Hookey L., & Fichtinger G. (2020). Automated segmentation of computed tomography colonography images using a 3D U-Net. SPIE Medical Imaging. DOI Google Scholar BibTeX
Ungi, T., Greer H., Sunderland K. R., Wu V., Baum Z. M. C., Schlenger C., et al. (2020). Automatic spine ultrasound segmentation for scoliosis visualization and measurement. IEEE Transactions on Biomedical Engineering. 67, 3234 - 3241. DOI Google Scholar BibTeX Ungi2020.pdf (676.48 KB)
Wu, C. O., Sunderland K. R., Filippov M., Sainsbury B., Fichtinger G., & Ungi T. (2020). Workflow for creation and evaluation of virtual nephrolithotomy training models. SPIE Medical Imaging Conference 2020. 11315, DOI Google Scholar BibTeX CWu2020a-manuscript.pdf (401.02 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. Google Scholar BibTeX Wu2020b.pdf (133.02 KB)
Wu, V., Ungi T., Sunderland K. R., Pigeau G., Schonewille A., & Fichtinger G. (2020). Automatic segmentation of spinal ultrasound landmarks with U-net using multiple consecutive images for input. SPIE Medical Imaging. DOI Google Scholar BibTeX Wu2020a.pdf (292.4 KB)
Laframboise, J., Ungi T., Sunderland K. R., Zevin B., & Fichtinger G. (2020). Open source platform for automated collection of training data to support video-based feedback in surgical simulators. SPIE Medical Imaging. Google Scholar BibTeX

2019
Lasso, A., Pinter C., Choueib S., Ungi T., & Fichtinger G. (2019). Enhance medical software applications with immersive virtual reality experience. Techna Symposium. Google Scholar BibTeX Lasso2019.pdf (1.05 MB)
Vaughan, T., Brastianos H., Ungi T., Lasso A., Falkson C., & Fichtinger G. (2019). Needle Navigation and Catheter Reconstruction for Breast Brachytherapy Using Open Source Software. Acta Polytechnica Hungarica. 16, 99-118. Google Scholar BibTeX Vaughan2019a.pdf (3.42 MB)
Hisey, R., Ungi T., Camire D., Erb J., Howes D., & Fichtinger G. (2019). Comparison of convolutional neural networks for central venous catheterization tool detection. Imaging Network of Ontario Symposium. Google Scholar BibTeX RHisey_ImNO2019.pdf (464.16 KB)
Laframboise, J., Ungi T., Lasso A., Asselin M., Holden M., Tan P., et al. (2019). Analyzing the curvature of the colon in different patient positions. SPIE Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling. 10951, Google Scholar BibTeX Laframboise2019a.pdf (400.26 KB)
Wiercigroch, J., Baum Z. M. C., Ungi T., Fritz J., & Fichtinger G. (2019). Validation of a low-cost adjustable, handheld needle guide for spine interventions. SPIE Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling. 10951, Google Scholar BibTeX Wiercigroch2019a.pdf (391.96 KB)
Lia, H., Baum Z. M. C., Vaughan T., Ungi T., McGregor T., & Fichtinger G. (2019). Usability and accuracy of an electromagnetically tracked partial nephrectomy navigation system. 17th Annual Imaging Network of Ontario Symposium (ImNO). Google Scholar BibTeX Lia2019a.pdf (164.12 KB)
Baum, Z. M. C., Church B., Lasso A., Ungi T., Schlenger C., Borschneck D. P., et al. (2019). Step-wise identification of ultrasound-visible anatomical landmarks for 3D visualization of scoliotic spine. SPIE Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling. 10951, Google Scholar BibTeX Baum2019a.pdf (496 KB)
Connolly, L., Ungi T., Lasso A., Vaughan T., Asselin M., Mousavi P., et al. (2019). Mechanically-Controlled Spectroscopic Imaging for Tissue Classification. SPIE Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling. 10951, DOI Google Scholar BibTeX Connolly2019a.pdf (877.7 KB)
Baum, Z. M. C., Lasso A., Ryan S., Ungi T., Rae E., Zevin B., et al. (2019). Augmented reality training platform for neurosurgical burr hole localization. Journal of Medical Robotics Research. 4, 1942001-1 - 1942001-13. DOI Google Scholar BibTeX Baum2020a.pdf (646.88 KB)
Baum, Z. M. C., Ryan S., Rae E., Lasso A., Ungi T., Levy R., et al. (2019). Assessment of intraoperative neurosurgical planning with the Microsoft HoloLens. 17th Annual Imaging Network Ontario Symposium (ImNO). Google Scholar BibTeX Baum2019b.pdf (162.89 KB)
Asselin, M., Kaufmann M., Wiercigroch J., Ungi T., Lasso A., Rudan J., et al. (2019). Navigated real-time molecular analysis in the operating theatre, demonstration of concept. SPIE Medical Imaging 2019. Google Scholar BibTeX
Perrin, S., Baum Z. M. C., Asselin M., Underwood G., Choueib S., Lia H., et al. (2019). Reproducibility of freehand calibrations for ultrasound-guided needle navigation. SPIE Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling. 10951, Google Scholar BibTeX Perrin2019a.pdf (686.56 KB)
Lund, S., Vaughan T., Ungi T., Lasso A., Asselin M., Yeo C., et al. (2019). Controlling virtual views in navigated breast conserving surgery. SPIE Medical Imaging 2019. Google Scholar BibTeX
Laframboise, J., Ungi T., Lasso A., Asselin M., Holden M., Tan P., et al. (2019). Quantifying the effect of patient position on the curvature of colons. 17th Annual Imaging Network Ontario Symposium (ImNO). Google Scholar BibTeX Laframboise2019b.pdf (198.44 KB)
Wu, V., Asselin M., Ungi T., & Fichtinger G. (2019). Detection of Spinal Ultrasound Landmarks Using Convolutional Neural Networks. 33rd International Congress & Exhibition on Computer Assisted Radiology and Surgery (CARS). 14, DOI Google Scholar BibTeX Wu2019b.pdf (213.21 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). Google Scholar BibTeX Wu2019a.pdf (158.09 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). Google Scholar BibTeX Isen2019b.pdf (129.5 KB)
Isen, J., Hisey R., Ungi T., & Fichtinger G. (2019). Retraining MobileNet with highly variable data for tool detection in central venous catheterization. 17th Annual Imaging Network Ontario Symposium (ImNO). Google Scholar BibTeX Isen2019a.pdf (3.12 MB)
House, R., Kunz M., Valiquette C., Lasso A., Ungi T., Rudan J., et al. (2019). Monitoring volume changes for breast reconstruction surgery using three dimensional optical surface scanning. Canadian Society of Plastic Surgeons (CSPS) Annual Meeting. Google Scholar BibTeX House2019a-manuscript.pdf (372.2 KB)

2018
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. DOI Google Scholar BibTeX Yeo2017.pdf (527.68 KB)
Holden, M., Zhao Y., Haegelen C., Essert C., Fernanez-Vidal S., Bardinet E., et al. (2018). Self-guided training for deep brain stimulation planning using objective assessment. International Journal of Computer Assisted Radiology and Surgery. 13, 1129-1139. DOI Google Scholar BibTeX
Holden, M., Lia H., Xia S., Keri Z., Ungi T., & Fichtinger G. (2018). Configurable Overall Skill Assessment in Ultrasound-Guided Needle Insertion. 16th Annual Imaging Network Ontario Symposium (ImNO). Google Scholar BibTeX Holden2018b.pdf (300.32 KB)
Asselin, M., Lasso A., Ungi T., & Fichtinger G. (2018). Towards webcam-based tracking for interventional navigation. SPIE Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling. Google Scholar BibTeX Asselin2018a.pdf (429.19 KB)

Pages