Overview
Topic status: We're looking for students to study this topic.
To make sense of the image data that results from a medical scan, it is first turned into a statistical map. After this, a statistical classification or segmentation of the pixels of the image can be carried out to take account of the noise present in the images. The aim of a statistical analysis might be to classify regions of the image as being from an area where there is or is not a tumour present, for example. Naturally, the statistical approach used for classification will influence the conclusions that are drawn from the image. Therefore, it is important to find analytical methods that are reliable and yet that are also fast and therefore feasible to implement. In this way, statistics plays an integral role in medical imaging research and clinical application of imaging. This project will use recent developments in computational Bayesian statistics to develop new techniques that are fast and reliable to implement.
- Study level
- PhD
- Supervisors
- QUT
- Organisational unit
Science and Engineering Faculty
- Research area
- Contact
- Please contact the supervisor.
Professor Tony Pettitt
