Antony Hodgson

Professor and Associate Head, Teaching

B.A.Sc.; M.A.Sc. (British Columbia); Ph.D. (MIT and Harvard University); Postdoctoral Fellowship (Clemson University); Associate Director, Institute for Computing, Information and Cognitive Systems; Associate Head of Teaching, Department of Mechanical Engineering

Research Interests

• Computer-Assisted Surgery
• Medical Robotics
• Surgical Simulators and Skill Assessment
• Neuromotor Control
• Biomechanics

Current Research Work

The primary focus of my work is on computer-assisted orthopaedic surgery; our main goal is to improve the accuracy of performing surgical tasks (such as placing implants or reducing fractures) while minimizing use of and exposure to radiation and decreasing operative time. We are currently working in three main areas:

• Using Ultrasound to Accurately Locate Bone Surfaces: The primary intraoperative imaging modality used in orthopaedic surgery is C-arm fluoroscopy, but this modality is intrinsically two-dimensional and can expose the patient and operating room team to ionizing radiation. Our goal is to use ultrasound instead, as it is a safe imaging technique that can generate intrinsically three-dimensional surface representations. The key applications are in trauma and spine surgery.
• Smart C-Arm Technologies: The C-arm fluoroscopy machine is a heavy and awkward device, and is not typically used to provide accurate, quantitative information to guide operative procedures. We are developing a suite of technologies aimed at making C-arms location aware and dramatically easier to maneuver so that surgeons can more accurately execute surgical actions and reduce both operative time and radiation exposure. We are also developing a C-arm-based Roentgen Stereophotogrammetry (RSA) system.
• Bone-Mounted Robots: The success of knee replacements depends significantly on the accuracy of placement of the implants, particularly in unicompartmental knee replacement procedures. Conventional navigation systems can improve accuracy compared with conventional techniques, but to date only small robotic devices have demonstrated reductions in operating time in total knee replacements. We are currently investigating a new design concept for a bone-mounted robot for unicompartmental procedures.

Selected Publications

• V. Zakeri, and A.J. Hodgson, “Automatic Identification of Hard and Soft Bone Tissues by Analyzing Drilling Sounds,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, 27(2), pp.404-414, 2019.
• R. Newell, H. Esfandiari, C. Anglin, R. Bernard, J. Street, and A.J. Hodgson, “An intraoperative fluoroscopic method to accurately measure the post-implantation position of pedicle screws,” International journal of computer assisted radiology and surgery, 13(8), pp.1257-1267, 2018.
• O. Paserin, K. Mulpuri, A. Cooper, A.J. Hodgson, and R. Garbi, “Real time RNN based 3D ultrasound scan adequacy for developmental dysplasia of the hip,” In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 365-373). Springer, Cham, 2018.
• P. Pandey, P. Guy, A.J. Hodgson, and R. Abugharbieh, “Fast and automatic bone segmentation and registration of 3D ultrasound to CT for the full pelvic anatomy: a comparative study,” International journal of computer assisted radiology and surgery, 13(10), pp.1515-1524, 2018.
• N. Quader, E.K. Schaeffer, A.J. Hodgson, R. Abugharbieh, and K. Mulpuri, “A Systematic Review and Meta-analysis on the Reproducibility of Ultrasound-based Metrics for Assessing Developmental Dysplasia of the Hip,” Journal of Pediatric Orthopaedics, 38(6), pp.e305-e311, 2018.
• H. Esfandiari, R. Newell, C. Anglin, J. Street, and A.J. Hodgson, “A deep learning framework for segmentation and pose estimation of pedicle screw implants based on C-arm fluoroscopy,” International journal of computer assisted radiology and surgery, 13(8), pp.1269-1282, 2018.
• T. Mohammad, Y.P. Liu, and A. Hodgson, “Effects of bracing on pointing task accuracy,” CMBES Proceedings, 37, 2018.
• O. Paserin, K. Mulpuri, A. Cooper, A.J. Hodgson, and R. Garbi, “Automated Dynamic 3D Ultrasound Assessment of Developmental Dysplasia of the Infant Hip,” In International Workshop on Computational Methods and Clinical Applications in Musculoskeletal Imaging (pp. 136-145). Springer, Cham, 2018.
• H. El-Hariri, P. Pandey, A.J. Hodgson, and R. Garbi, “Augmented reality visualisation for orthopaedic surgical guidance with pre-and intra-operative multimodal image data fusion,” Healthcare Technology Letters, 5(5), pp.189-193, 2018.
• X. Kang, D.R. Wilson, and A.J. Hodgson, “Evaluating in vivo bone motion of hip joints under weight-bearing condition using open MRI,” CMBES Proceedings, 37, 2018.
• H. Esfandiari, C. Anglin, P. Guy, and A.J. Hodgson, “A deep learning-based approach for localization of pedicle regions in preoperative CT scans,” CAOS, 2, pp.46-50, 2018.
• N. Quader, A.J. Hodgson, K. Mulpuri, E. Schaeffer, and R. Abugharbieh, “Automatic evaluation of scan adequacy and dysplasia metrics in 2-D ultrasound images of the neonatal hip,” Ultrasound in medicine & biology, 43(6), pp.1252-1262, 2017.
• M.A. Hussain, A.J. Hodgson, and R. Abugharbieh, “Strain-initialized robust bone surface detection in 3-D ultrasound,” Ultrasound in medicine & biology, 43(3), pp.648-661, 2017.
• O. Paserin, K. Mulpuri, A. Cooper, A.J. Hodgson, and R. Abugharbieh, “Automatic near real-time evaluation of 3D ultrasound scan adequacy for developmental dysplasia of the hip,” In Computer Assisted and Robotic Endoscopy and Clinical Image-Based Procedures (pp. 124-132). Springer, Cham, 2017.
• N. Quader, A.J. Hodgson, K. Mulpuri, A. Cooper, and R. Abugharbieh, “A 3D femoral head coverage metric for enhanced reliability in diagnosing hip dysplasia,” In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 100-107). Springer, Cham, 2017.
• N. Quader, A.J. Hodgson, K. Mulpuri, A. Cooper, and R. Abugharbieh, “Towards reliable automatic characterization of neonatal hip dysplasia from 3D ultrasound images,” In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 602-609). Springer, Cham, 2016.
• I. Hacihaliloglu, P. Guy, A.J. Hodgson, and R. Abugharbieh, “Automatic extraction of bone surfaces from 3D ultrasound images in orthopaedic trauma cases,” International journal of computer assisted radiology and surgery, 10(8), pp.1279-1287, 2015.
• N. Quader, A.J. Hodgson, K. Mulpuri, T. Savage, and R. Abugharbieh, “Automatic assessment of developmental dysplasia of the hip,” In 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI) (pp. 13-16). IEEE, 2015.
• A. Brounstein, I. Hacihaliloglu, P. Guy, A.J. Hodgson, and R. Abugharbieh, “Fast and accurate data extraction for near real-time registration of 3-D ultrasound and computed tomography in orthopedic surgery,” Ultrasound in medicine & biology, 41(12), pp.3194-3204, 2015.
• F. Gheorghe, A.J. Hodgson, and H.F. Van der Loos, “BRIDGING THE’VALLEY OF DEATH’IN PRODUCT DEVELOPMENT: A CASE STUDY OF THE DRILL COVER PROJECT,” In DS 80-6 Proceedings of the 20th International Conference on Engineering Design (ICED 15) Vol 6: Design Methods and Tools-Part 2 Milan, Italy, 27-30.07. 15, 2015.
• I. Hacihaliloglu, P. Guy, A. J. Hodgson, and R. Abugharbieh, “Volume-specific parameter optimization of 3D local phase features for improved extraction of bone surfaces in ultrasound,” The International Journal of Medical Robotics and Computer Assisted Surgery, 2014.
• A. J. Hodgson, R. C. Tam, and H. M. Van der Loos, “‘ Engineers in Scrubs’-A New Graduate Training Program for Biomedical Engineers at the University of British Columbia,” Journal of Medical Devices, 2014.
• F. Gheorghe, A. J. Hodgson, and H. M. Van der Loos, “IMPROVING OUTCOMES IN STUDENT DESIGN COURSES THROUGH QUALITATIVE USER RESEARCH AND CONTEXTUAL IMMERSION,” Proceedings of the Canadian Engineering Education Association, 2013.
• X. Kang, H. Zhang, D. Garbuz, D. R. Wilson, and A. J. Hodgson, “Preliminary evaluation of an MRI-based technique for displaying and quantifying bony deformities in cam-type femoroacetabular impingement,” International journal of computer assisted radiology and surgery, vol. 8, no. 6, pp. 967–975, 2013.
• A. Amir-Khalili, A. J. Hodgson, and R. Abugharbieh, “Real-time extraction of local phase features from volumetric medical image data,” in Biomedical Imaging (ISBI), 2013 IEEE 10th International Symposium on, 2013, pp. 930–933.
• A. J. Hodgson and H. M. Van der Loos, “The Innovation Agenda: Potential Implications for the Engineering Design Curriculum,” Proceedings of the Canadian Engineering Education Association, 2013.
• I. Hacihaliloglu, R. Abugharbieh, A. J. Hodgson, R. N. Rohling, and P. Guy, “Automatic bone localization and fracture detection from volumetric ultrasound images using 3-d local phase features,” Ultrasound in medicine & biology, vol. 38, no. 1, pp. 128–144, 2012.
• N. Hungr, B. Roger, A. J. Hodgson, and C. Plaskos, “Dynamic physical constraints: emulating hard surfaces with high realism,” Haptics, IEEE Transactions on, vol. 5, no. 1, pp. 48–57, 2012.
• A. J. Hodgson and H. M. Van Der Loos, “ASSESSMENT OF EVIDENCE FOR THE EFFECTIVENESS OF DIFFERENT IDEATION PRACTICES,” Proceedings of the Canadian Engineering Education Association, 2012.
• I. Hacihaliloglu, R. Abugharbieh, A. J. Hodgson, and R. N. Rohling, “Automatic adaptive parameterization in local phase feature-based bone segmentation in ultrasound,” Ultrasound in medicine & biology, vol. 37, no. 10, pp. 1689–1703, 2011.

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