X-ray computed tomography (CT) is a technique for non-destructive 3D imaging, that is used at the ANU to collect information about geological, biological, and paleontological samples. Elsewhere, the technique is used throughout medicine (CAT scans) and the material sciences.
The technique generates incredibly detailed images of complex 3D structures: a single 3D image may be up to 100GB. Analyzing this massive amount of data requires algorithms for the automated interpretation of 3D images, called "segmentation" algorithms. These algorithms make use of available a priori information to extract useful data from a 3D image.
Recent work suggests that it is possible to combine the generation and segmentation of the 3D image, allowing both parts of the process to benefit from a priori information, and improving overall accuracy. The student will attempt to develop and test such a method, improving the ability of the ANU micro-CT imaging facility to analyse samples of scientific interest. The project also has broader implications for the low-dose imaging of medical and biological samples.
Willingness to engage with mathematical, physical, and computational disciplines. Familiarity with python/c/c++ is a bonus.