Thomas Fevens
Adjunct Professor, Department of Surgery
THOMAS FEVENS, PhD, is an Associate Professor and Associate Chair, Computer Science and Software Engineering, at Concordia University, and an Adjunct Professor, Dept. of Surgery, at 污污草莓视频. While at Queen's University, Dr. Fevens obtained an MSc and a PhD in Computing and Information Science in 1999, specializing in Numerical Analysis and Computational Geometry, respectively, also having a BSc and an MSc in Physics from Queen's. He was a Postdoctoral Fellow at 污污草莓视频 from 2000 to 2001 in the School of Computer Science. An expert in Artificial Intelligence (AI), Deep Learning and Medical Imaging, he has published articles in top venues such as ICCV, MICCAI, and IEEE TMI on Computer-Aided Breast Cancer Malignancy Classification, Clinical Image Segmentation, and Deep Learning for Medical Imagery. His areas of research also include Biometrics Analysis, Assistive Technology, and Computer Networks.
Three-Dimensional (3D) Animation and Calculation for the Assessment of Engaging Hill-Sachs Lesions With Computed Tomography 3D Reconstruction J Tat, J Crawford, J Chong, T Powell, TG Fevens, T Popa, PA Martineau Arthroscopy, sports medicine, and rehabilitation 3 (1), e89-e96, 2021.
From the Gaming Console to the Field: Using the Microsoft Kinect as a Portable and Accurate tool for Assessing of Jumping Dynamics N Karatzas, J Corban, S Bergeron, T Fevens, LN Veilleux, PA Martineau Zeitschrift f眉r Orthop盲die und Unfallchirurgie 158 (S 01), DKOU20-318, 2020.
Using the Microsoft Kinect to Determine risk of ACL injury in Varsity Athletes: A Paradigm Shift in Pre-season Physical Assessment N Karatzas, J Corban, S Bergeron, T Fevens, PA Martineau Zeitschrift f眉r Orthop盲die und Unfallchirurgie 158 (S 01), DKOU20-310, 2020.
Rafiee L., Fevens T. (2020) Unsupervised Anomaly Detection with a GAN Augmented Autoencoder. In: Farkas I., Masulli P., Wermter S. (eds) Artificial Neural Networks and Machine Learning - ICANN 2020. ICANN 2020. Lecture Notes in Computer Science, vol 12396. Springer, Cham.
P. Chalangari, T. Fevens and H. Rivaz, "3D Human Knee Flexion Angle Estimation Using Deep Convolutional Neural Networks*," 2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2020, pp. 5424-5427.
FoCL: Feature-Oriented Continual Learning for Generative Models Q Lao, M Mortazavi, M Tahaei, F Dutil, T Fevens, M Havaei arXiv preprint arXiv:2003.03877, 2020
Kang Q., Lao Q., Fevens T. (2019) Nuclei Segmentation in Histopathological Images Using Two-Stage Learning. In: Shen D. et al. (eds) Medical Image Computing and Computer Assisted Intervention - MICCAI 2019. MICCAI 2019. Lecture Notes in Computer Science, vol 11764. Springer, Cham.
Cell phenotype classification using deep residual network and its variants Q Lao, T Fevens International Journal of Pattern Recognition and Artificial Intelligence 2019 33:11.
Miselis B., Fevens T., Krzyżak A., Kowal M., Monczak R. (2020) Deep Neural Networks for Breast Cancer Diagnosis: Fine Needle Biopsy Scenario. In: Korbicz J., Maniewski R., Patan K., Kowal M. (eds) Current Trends in Biomedical Engineering and Bioimages Analysis. PCBEE 2019. Advances in Intelligent Systems and Computing, vol 1033. Springer, Cham.
Dual Adversarial Inference for Text-to-Image Synthesis Qicheng Lao, Mohammad Havaei, Ahmad Pesaranghader, Francis Dutil, Lisa Di Jorio, Thomas Fevens; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2019, pp. 7567-7576.
Q. Lao, T. Fevens and B. Wang, "Leveraging Disease Progression Learning for Medical Image Recognition," 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2018, pp. 671-675.