Honours Projects 2008

Projects supervised by Lingfeng Wen and David Feng

Information technology in biomedicine (ITB) has substantially improved clinical diagnosis and delivered significant benefits to healthcare systems. Advances in ITB not only offer more accurate medical data for visualisation and efficient management of large amount of data, and also fascinate incorporation of artificial intelligence and development of information system, to identify new knowledge and provide objective information for clinical diagnosis. The following projects will involve diverse technologies to deal with the state-of-art medical imaging data, and develop new methodologies to address clinical challenges.
Students involved in the projects will have the opportunity to access the up-to-date technology of molecular and anatomical imaging, and also to work in the Royal Prince Alfred hospital for a certain period of time depending on the progress. The projects may be extended as PH.D topics.

Please address your queries to lwen AT usyd DOT edu DOT au

Advanced computer modelling of biological systems using insight knowledge
Computer modelling techniques, which employ information technology to build abstracted mathematical model, have been widely used to describe behaviours of real systems and predict future trends in the many areas such as finance, entertainment, and meteorology. In the area of biomedicine, modelling techniques have also been applied to disclose quantitatively interactions between functional process and physiological system. This project will be initialized from current modelling techniques and advance the models for case-oriented purpose with new knowledge from medical images. The project will foster the abilities of image analysis, system design and integration, data simulation and team collaboration.

Discovery of new image-derived features for computer-aided diagnosis
Computer-aided diagnosis (CAD) is one important area in the areas of ITB by using artificial intelligence and advanced technologies in providing objective evaluation and serving as a second reader to avoid operator-dependent biases. This project will investigate how to employ IT approaches to discover new image-derived features and achieve better diagnosis for specific disorders. The involved students will gain the experiences like segmentation, registration and data mining, and also improve their skills of problem solving and gain an insight into digital image analysis.

Non-invasive information extraction for functional imaging
Quantitative parameter estimation in functional imaging requires invasive blood sampling to obtain the input function for kinetic analysis. However, invasive blood sampling may lead to some medical problems and give rise to patient’ discomfort, which is not suitable for clinical routine. This project will develop a new non-invasive method for better extraction of intrinsic physiological values using advanced information technologies to tackle the challenging clinical issue. The project will foster the abilities of image interpretation, kinetic analysis, parameter estimation, and system design. The developed method will be integrated into a hospital information system for clinical routine.

Accurate information restoration for multi-modality imaging
The state-of-art multi-modality imaging system provides a unique approach visualizing structural and functional changes at the same time. However, the different characteristics of imaging modalities may cause the losses of quantification and severe discrepancy between the images, which may hinder accurate diagnosis. This project will aim to develop a new method for addressing the challenges by using the information extracted from the images with the aid of advanced technologies. The involved students will gain the experiences such as image analysis, modelling technique, computer simulation as well as the improvement of skills like problem solving.