Songbai Ji
The biomechanical mechanisms behind traumatic brain injury (TBI) have been an active research focus for more than 70 years. However, the field is still largely focused on impact kinematics or estimated brain responses in generic regions from single head impact to predict a binary brain injury status on a population basis. An important research focus in my lab is to integrate advanced neuroimaging into TBI biomechanics research to understand injuries to functionally important neural pathways. At the same time, we develop techniques to achieve near real-time response feedbacks. This is critical to enable the model for studying the cumulative effects from repetitive head impacts for athletes participating in contact sports using their individualized impact exposure. Ultimately, we hope that these efforts could lead to a tool feasible for clinical concussion diagnostics.
In parallel, I have a strong interest and research experience in surgical image-guidance in open-skull neurosurgery and open spinal surgery. Accurate patient registration is the cornerstone for successful image-guidance. My lab works with other engineers and clinicians to establish techniques for accurate and robust patient registration using low-cost, radiation-free intraoperative images. The goal is to accelerate the adoption of image-guidance especially in spine surgery where the use of the technique is low primarily due to challenges in patient registration.
Both lines of research rely heavily on computational modeling and medical imaging.
Songbai Ji
The biomechanical mechanisms behind traumatic brain injury (TBI) have been an active research focus for more than 70 years. However, the field is still largely focused on impact kinematics or estimated brain responses in generic regions from single head impact to predict a binary brain injury status on a population basis. An important research focus in my lab is to integrate advanced neuroimaging into TBI biomechanics research to understand injuries to functionally important neural pathways. At the same time, we develop techniques to achieve near real-time response feedbacks. This is critical to enable the model for studying the cumulative effects from repetitive head impacts for athletes participating in contact sports using their individualized impact exposure. Ultimately, we hope that these efforts could lead to a tool feasible for clinical concussion diagnostics.
In parallel, I have a strong interest and research experience in surgical image-guidance in open-skull neurosurgery and open spinal surgery. Accurate patient registration is the cornerstone for successful image-guidance. My lab works with other engineers and clinicians to establish techniques for accurate and robust patient registration using low-cost, radiation-free intraoperative images. The goal is to accelerate the adoption of image-guidance especially in spine surgery where the use of the technique is low primarily due to challenges in patient registration.
Both lines of research rely heavily on computational modeling and medical imaging.
Scholarly Work
Ji, S., Fan, X., Paulsen, K., Roberts, D., Mirza, S. K., and Lollis, S. S., 2015, “Patient Registration Using Intraoperative Stereovision in Image-guided Open Spinal Surgery,” IEEE Trans. Biomed. Eng., 62(9), pp. 2177–2186. (monthly highlight)
Cai, Y., Olson, J. D., Fan, X., Evans, L., Paulsen, K. D., Roberts, D. W., Mirza, S. K., Lollis, S. S., and Ji, S., 2016, “Automatic Geometric Rectification for Patient Registration Using Stereovision in Image-guided Spine Surgery,” SPIE Medical Imaging.