After receiving his M.Sc. in Geomatics Engineering (specializing in digital imaging systems) form the University of Calgary, Canada in 2014, Hooman started his doctoral studies at the University of British Columbia, Canada in Biomedical Engineering and finished his PhD program in 2020. Hooman has joined our group as a postdoctoral fellow ever since and will be involved in a number of projects related to computer assisted orthopaedic surgery and medical image analysis.
- Roth T, Carrillo F, Wieczorek W, Ceschi G, Esfandiari H, Sutter R, Vlachopoulos L, Wein W, Fucentese SF, Fürnstahl P. Three-dimensional preoperative planning in the weight-bearing state: validation and clinical evaluation. Insights into Imaging, 2021.
- Esfandiari H, Weidert S, Kövesházi I, Anglin C, Street J, Hodgson AJ. Deep learning-based X-ray inpainting for improving spinal 2D-3D registration. Int J Med Robot. 2021
- Esfandiari H, Anglin C, Guy P, Street J, Weidert S, Hodgson AJ. A comparative analysis of intensity-based 2D-3D registration for intraoperative use in pedicle screw insertion surgeries. Int J Comput Assist Radiol Surg. 2019
- Esfandiari H, Newell R, Anglin C, Street J, Hodgson AJ. A deep learning framework for segmentation and pose estimation of pedicle screw implants based on C-arm fluoroscopy. Int J Comput Assist Radiol Surg. 2018
- Esfandiari H, Amiri S, Lichti DD, Anglin C. A fast, accurate and closed-form method for pose recognition of an intramedullary nail using a tracked C-arm. Int J Comput Assist Radiol Surg. 2016
- Esfandiari H, Andreß S, Herold M, Böcker W, Weidert S, Hodgson AJ. A Deep Learning Approach for Single Shot C-Arm Pose Estimation. CAOS. 2020
- Esfandiari H, Anglin C, Guy P, Hodgson AJ. A deep learning-based approach for localization of pedicle regions in preoperative CT scans. CAOS. 2018
- Esfandiari H, Martinez J, Alvarez AG, Street J, Anglin C, Hodgson AJ. An automated, robust and closed form mini-RSA system for intraoperative C-arm calibration. Int J Comput Assist Radiol Surg. 2017