Development Of A Non-invasive Magnetic Resonance Based Cartilage Damage Assessment Technique
Funder
National Health and Medical Research Council
Funding Amount
$556,131.00
Summary
This project will develop automated methods for the extraction of 3D maps of cartilage, bone and other anatomy from high field Magnetic Resonance Images of joints in the body.
MR Hip Intervention And Planning System To Enhance Clinical And Surgical Outcomes
Funder
National Health and Medical Research Council
Funding Amount
$668,069.00
Summary
Degenerative hip disorders and osteoarthritis are a major cause of chronic pain and disability. This project will develop a software tool that allows clinicians to assess, monitor and plan patient treatment using magnetic resonance imaging. It will be the first tool that models joint motion using assessments of bone, cartilage and labral tissue. This will help guide treatment selection and improve outcomes from hip surgeries performed on over 20,000 Australians each year.
Low Cost Smart Screening System For Sight Threatening Eye Disease: Diabetic Retinopathy
Funder
National Health and Medical Research Council
Funding Amount
$529,079.00
Summary
The aim of the project is to develop an automated disease grading and clinical decision support system for diabetic retinopathy (DR) to perform eye screening by primary care providers and nurses. The grading system will automatically extract DR pathology from a patient’s color fundus images by image processing, feature detection and machine learning algorithms. Based on the detected information, the system can classify the patient as non symptom or a specific disease level.
Development Of The Listening In Spatialized Noise - Tonal Test (or LiSN-T)
Funder
National Health and Medical Research Council
Funding Amount
$227,136.00
Summary
In this project a novel listening test software will be developed for diagnosing spatial processing disorder in children. These children often have difficulties in understanding teachers in classrooms, which can significantly impact their ability to learn. The developed software will be specifically designed for diagnosing 5-year old children, before they enter primary school, and in contrast to existing tests will be independent of their language background.