gabor

Name

Gabor Fichtinger Dr. Univ., Director; Professor and Canada Research Chair (Tier 1)

Short Biography

Gabor Fichtinger received BSc and MSc degrees in Electrical Engineering, and Doctoral degree in Computer Science from the Technical University of Budapest, Hungary, in 1986, 1988, and 1990, respectively. He has a balanced academic, industrial, and clinical background in the development and clinical inauguration of image-guided surgery and interventional navigation systems. His specialty is image-guided needle-placement procedures, primarily for cancer diagnosis and therapy and musculoskeletal conditions. Dr. Fichtinger is a Professor of Computer Science, with cross appointments in Electrical and Computer Engineering, Mechanical and Materials Engineering, Surgery and Pathology at Queen’s University, Canada, with adjunct appointments at the Johns Hopkins University, USA, Western University, Canada and the medical University of Vienna, Austria. Dr. Fichtinger holds a Cancer Ontario Research Chair in Cancer Imaging.

Affiliation

Institution: Queen's University

Department: School of Computing

Designation: Faculty

Lab membership period: Professor, Cancer Care Ontario Research Chair

Projects

Publications

2021
O'Driscoll, O., Hisey R., Camire D., Erb J., Howes D., Fichtinger G., et al. (2021). Object detection to compute performance metrics for skill assessment in central venous catheterization. SPIE Medical Imaging. Google Scholar BibTeX ODriscoll2021a.pdf (322.11 KB)
O'Driscoll, O., Hisey R., Camire D., Erb J., Howes D., Fichtinger G., et al. (2021). Surgical tool tracking with object detection for performance assessment in central venous catheterization. Imaging Network of Ontario Symposium. Google Scholar BibTeX ODriscoll2021b.pdf (151.14 KB)

2020
Connolly, L., Jamzad A., Kaufmann M., Rubino R., Sedghi A., Ungi T., et al. (2020). Classification of tumor signatures from electrosurgical vapors using mass spectrometry and machine learning: a feasibility study. Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions and Modeling. 11315, DOI Google Scholar BibTeX Connolly2020a.pdf (823.25 KB)
Wiercigroch, J., Hashtrudi-Zaad K., Ungi T., Bisleri G., & Fichtinger G. (2020). Force and torque feedback in endoscopic vessel harvesting. Medical Imaging 2020: Image-Guided Procedures, Robotic Inverventions and Modeling. 11315, DOI Google Scholar BibTeX Wiercigroch2020a.pdf (401.53 KB)
Gauvin, G., Yeo C. T., Ungi T., Merchant S., Lasso A., Jabs D., et al. (2020). Real‐time electromagnetic navigation for breast‐conserving surgery using NaviKnife technology: A matched case‐control study. The Breast Journal. 26, 399-405. DOI Google Scholar BibTeX
Hisey, R., Chen B., Camire D., Erb J., Howes D., Fichtinger G., et al. (2020). Recognizing workflow tasks in central venous catheterization using convolutional neural networks and reinforcement learning. International Conference on Computer Assisted Radiology and Surgery. 94-95. Google Scholar BibTeX RHisey_CARS_2020.pdf (152.24 KB)
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)
Pinter, C., Olding T., L. Schreiner J., & Fichtinger G. (2020). Using Fuzzy Logics to Determine Optimal Oversampling Factor for Voxelizing 3D Surfaces in Radiation Therapy. Soft Computing. DOI Google Scholar BibTeX Pinter2020a.pdf (713.06 KB)
Pinter, C., Lasso A., Choueib S., Asselin M., Fillion-Robin J-CC., Vimort J-B., et al. (2020). SlicerVR for Medical Intervention Training and Planning in Immersive Virtual Reality. IEEE Transactions on Medical Robotics and Bionics. 2, 108-117. DOI Google Scholar BibTeX Pinter2020.pdf (521.6 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)
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)
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
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)
Barr, C., Lasso A., Asselin M., Pieper S., Robertson F. C., Gormley W. B., et al. (2020). Towards portable image guidance and automatic patient registration using an RGB-D camera and video projector. Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions and Modeling. 11315, DOI Google Scholar BibTeX Barr2020.pdf (487.62 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
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)
Choi, P. S., Nam HH., Lasso A., Herz C., Drouin S., Harrild D. M., et al. (2020). 3D Modeling of Surgically Implanted Stent-Based Valves in the Mitral Position in Children. The Annals of Thoracic Surgery. DOI 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)
Pinter, C., Lasso A., Asselin M., Fillion-Robin J-CC., Vimort J-B., Martin K., et al. (2019). SlicerVR for image-guided therapy planning in immersive virtual reality. The 12th Hamlyn Symposium on Medical Robotics, 23-26 June 2019, Imperial College, London, UK. 91-92. Google Scholar BibTeX Pinter2019a.pdf (348.83 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)
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)
Choueib, S., Pinter C., Lasso A., Fillion-Robin J-CC., Vimort J-B., Martin K., et al. (2019). Assessment of immersive medical virtual reality visualization using 3D Slicer. 17th Annual Imaging Network Ontario Symposium (ImNO). Google Scholar BibTeX Choueib2019b.pdf (314.46 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)
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)
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)
Choueib, S., Pinter C., Lasso A., Fillion-Robin J-CC., Vimort J-B., Martin K., et al. (2019). Evaluation of 3D Slicer as a medical virtual reality visualization platform. SPIE Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling. 10951, Google Scholar BibTeX Choueib2019a.pdf (746.97 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)
Pinter, C., Lasso A., & Fichtinger G. (2019). Polymorph Segmentation Representation for Medical Image Computing. Computer Methods and Programs in Biomedicine. 171, 19-26. DOI Google Scholar BibTeX Pinter2019_Manuscript.pdf (707.26 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)

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