This proposed research aims at developing a fully automated computerized system for multiple spinal disease diagnosis. It improves the efficiency of the current clinically workflow. The development of the research is based on the state-of-the-art computer vision and image processing techniques. To the best of our knowledge, our group is the first group focusing on this direction. Once success, it will not only improve the clinician’s accuracy, inter and intraobservability, but also promote the technical advancement in the computer vision and image processing.
The proposed research is to design, develop and validate an artificial ear-canal that simulates the electrical noise conditions that exist when taking EVestG measurements by associated bio-signal amplifiers. Such a simulator will allow the rapid, rational and accurate refinement of such amplifiers and tympanic electrode; it will also allow improvements to be made to the developed signal extraction software algorithms.
Surgical training is increasingly being done using simulator technology in order to teach basic skills to residents without risking patients’ lives. However, neurosurgery lags behind other surgical specialties in the adoption of simulators. Since there are no commercial simulators in this domain, the National Research Council has embarked on a neurosurgery simulator development program, in collaboration with Canadian neurosurgeons.
In our experiments with semiconductor microstructures, such as those used for the fabrication of light emitting diodes (LED), our team has discovered that popular LED devices could also be used for the detection of micro-organisms that come in contact with the device. As a result of our almost 5 years of research, we have demonstrated the operation of an LED-like photonic biosensor capable of rapid (less than 2 hours) detection of E. coli.
This study will investigate the process of information technology adoption within the Canadian health care system in order to uncover the underlying promoters and barriers to technology implementation. The knowledge gained from this study will assist McKesson and other health IT companies to adjust their technologies and deployment strategies for effective technology implementation. Ultimately, more effective technology implementation will result in more efficient workflows and health are delivery.
Positron Emission Tomography (PET) images need correction for the loss of photons. This loss, or attenuation, is due to interactions with patient tissues. Corrections are currently done with X-ray Computed Tomography (CT), however we are proposing a method whereby Magnetic Resonance Images (MRI) are used. This will be done by creating an attenuation map(?-map). The construction of ?-maps can be divided into two categories, patient specific ?-maps by MRI segmentation, and registration of a predefined atlas to an MRI.
This project aims at developing a computerized system for spine diagnosis. This system will improve the efficiency and efficacy of radiologists to diagnose patients’ spine problems. The development of the system involves devising a set of tailor-made mathematical formulation. These formulation are grounded on the state-of-the-art computer vision algorithms and they are capable of capturing the knowledge required during spine diagnosis. The computerized system employing these mathematical formulations will be able to mimic the human expert to perform basic image-based diagnosis of spine.
In Computed Tomography (CT), X-ray radiation is used to penetrate through the internal structure of the patient body in order to produce digital images. Therefore patient could be exposed to certain level of X-ray radiation dose. Accumulation of these exposures beyond certain threshold could increase risk of fatal cancer. Thus it is of paramount importance to lower the amount of radiation exposure during CT images acquisition. However, a low radiation dose in CT images would result to lower image quality.
This project seeks to improve the performance of polymer-based spinal implants through the development of a multi-layered coating technology to overcome identified problems. The coating must allow for: a) strong adhesion to the underlying polymer to ensure structural stability; b) radio-opaque properties to allow visualization of the implant during x-ray procedures; c) a bone bonding interface to support biological integration.