Special Research Initiatives - Grant ID: SR0354734
Funder
Australian Research Council
Funding Amount
$10,000.00
Summary
The Australian Research Network for Medical Devices: advanced technology solutions for patients and practitioners. Medical Device technologies embrace a wide range of scientific, engineering and medical knowledge, with the goal of assisting a clinical professional (doctor or nurse) deliver a service to a patient in an efficacious, cost effective manner. Development of appropriate medical devices, whether for diagnosis, treatment or prevention of disease or disability, is critical to improving h ....The Australian Research Network for Medical Devices: advanced technology solutions for patients and practitioners. Medical Device technologies embrace a wide range of scientific, engineering and medical knowledge, with the goal of assisting a clinical professional (doctor or nurse) deliver a service to a patient in an efficacious, cost effective manner. Development of appropriate medical devices, whether for diagnosis, treatment or prevention of disease or disability, is critical to improving health care and reducing health care costs. To be successful, a device must include all relevant disciplines in the research, development and testing phases. This network will bring together these groups, promoting knowledge sharing and cross-disciplinary investigations that illuminate current device limitations and potential solutions.Read moreRead less
Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features t ....Automated analysis of multi-modal medical data using deep belief networks. This project will develop an improved breast cancer computer-aided diagnosis (CAD) system that incorporates mammography, ultrasound and magnetic resonance imaging. This system will be based on recently developed deep learning techniques, which have the capacity to process multi-modal data in a unified and optimal manner. The advantage of this technique is that it is able to automatically learn both the relevant features to analyse in each modality and the hidden relationships between them. The use of deep belief networks has produced promising results in several fields, such as speech recognition, and so this project believes that our approach has the potential to improve both the sensitivity and specificity of breast cancer detection.Read moreRead less