The digital and bio-mechanical analysis of human motion is an attractive research field as it helps one understand and interpret pathologies affecting the body’s articular components. The goal of this project is to develop data analysis and automatic classification methods to differentiate between data from asymptomatic and pathological individuals. The data will be drawn from 3D morpho-functional assessments. Developed methods could eventually be considered for the creation of decision support and pathology diagnosis tools.
Currently, surgeons often reconstruct the middle ear to restore hearing with artificial prostheses that reconnect the middle ear bones that have been destroyed. This process is unpredictable and these prostheses are available in hundreds of different forms from many companies. The supervisor of this project runs one of the foremost laboratories in the world in exploring the vibration transmission properties of prostheses.
This project involves studying the kinematics of the human body during physical therapies on the arm and shoulder. With guidance and assistance from Glenrose Hospital, the intern will collect a library of typically prescribed motions of the shoulder and arm during physical therapy. He will then develop a mathematical model to represent the kinematics of the arm and shoulder as well as a parameter identification routine to identify the model parameters using simple moves and coordinate measurement techniques.
Medical image registration is the task of bringing two images into spatial alignment. Automatic and accurate 3D co-registration of nuclear medicine 3D image data with 3D anatomical data is crucial for improving the functional image reconstruction through anatomy-based attenuation correction. Co-registration is also important for the fusion of anatomical data with functional information. Most registration methods involve optimizing an intensity-based similarity metric that is defined by the transformation parameters.
Existing screening techniques for detecting breast cancer like X-ray Mammography, Magnetic Resonance Imaging (MRI), and Computer Assisted Tomography (CT) have some drawbacks, such as the inability to detect cancer at early stage, over sensitivity or requirement of breast compression. A new approach that has the potential to overcome these shortcomings is Ultra Wide Band (UWB) microwave imaging. This imaging method is based on solving Maxwell’s equation to determine dielectric properties profile with known electric field measured by antennas surrounding the breast.