Dielectric contrast imaging for 7 Tesla magnetic resonance applications. This project aims to develop novel radio-frequency (RF) technology, ensuring that the benefits of high-field magnetic resonance imaging (MRI) are available for a broader range of applications. This project will develop a new contrast mechanism directly related to the RF properties of individual tissue types, circumventing a limitation of intensity based imaging. This technology will enhance Australia’s global impact the dev ....Dielectric contrast imaging for 7 Tesla magnetic resonance applications. This project aims to develop novel radio-frequency (RF) technology, ensuring that the benefits of high-field magnetic resonance imaging (MRI) are available for a broader range of applications. This project will develop a new contrast mechanism directly related to the RF properties of individual tissue types, circumventing a limitation of intensity based imaging. This technology will enhance Australia’s global impact the development of imaging technology for healthcare, biomedical research and advanced diagnostics.Read moreRead less
Image-guided skin microbiopsy technology development. There is a need for targeted biopsies in dermatology. This novel technology enables minimally invasive biopsies to be taken from suspicious skin lesions by integrating micromedical and imaging devices.
New entropy measures of short term signals for smart wearable devices. This project aims to improve reliability and accuracy of wearable devices by developing a new set of computationally efficient algorithms. Wearable devices can be very effective in remote and continuous monitoring to detect short or bursty anomalous events. Present devices are unable to detect such events effectively due to limited capability in processing short length signal. This project will provide computationally efficie ....New entropy measures of short term signals for smart wearable devices. This project aims to improve reliability and accuracy of wearable devices by developing a new set of computationally efficient algorithms. Wearable devices can be very effective in remote and continuous monitoring to detect short or bursty anomalous events. Present devices are unable to detect such events effectively due to limited capability in processing short length signal. This project will provide computationally efficient algorithms for signal quality analysis and enhanced feature extraction methods in resource constrained wearable devices. This will improve the reliability and performance of wearable devices for adoption in intelligent decision-making systems.Read moreRead less