Science, Methods, and Technology
Application of computational models in orthopedic is not new to this field. Advances in medical imaging and introduction of the data-driven models to the field of medicine, however, significantly improved the techniques through which musculoskeletal condition can be quantitatively analyzed and explored.
Our research at the orthopedic engineering lab focuses on image processing, biomedical data science, function and motion analysis, and computational modeling of the musculoskeletal system.
Current medical imaging modalities allows quantifying parameters that can be used as biomarkers to assess the current state of the condition. Our research uses image post-processing and mathematical concepts to quantify the imaging information in different musculoskeletal conditions. The image modalities we use includes: computer tomography, magnetic resonance imaging (Dixon, UTE, T1-rho), 2D/3D ultrasonic imaging, and stereoradiography.
Machine learning and AIS
Our imaging research allows extracting numerous variables in individuals longitudinally. Application of the sensors and mobile apps to make smarter medical devices also provide valuable information regarding the patient condition. Machine learning concepts can use all these information to enhance diagnosis and personalized treatment in pediatric orthopedics.
We develop data- driven decision making tools using machine learning and deep learning. Situated in the Children's Hospital of Philadelphia, we use real patient data to validate and improve our models.
Function and Motion analysis
The ultimate goal of orthopedic interventions is to normalize the function of the musculoskeletal system. While medical imaging provides a static picture of the system, gait and motion analysis can generate information about real life activities such as walking and running. We use statistical methods to evaluate healthy versus diseased state of the musculoskeletal system through quantifying time-dependent variables of motion.
Sport medicine particularly benefits from gait and performance analysis. Dynamic analysis of the joint kinematics in sport medicine related injuries can prevent future injuries or improve the athlete performance.
Advanced computational concepts can be used to study complex systems such as musculoskeletal system. Our research aims to improve our understanding of human growth, growth abnormalities, and the reciprocal changes to the surgical interventions to improve therapeutics and care for musculoskeletal deformities.