This project is focused on the development of new computational approaches to resolve some fundamental problems related to the extraction of quantifiable information from microscopy images. The aim is to investigate and develop “intelligent” procedures and work-flows best suited for the analysis of microscopy images of cells and tissues (e.g. for the diagnosis of cancer). To this purpose, the researcher will investigate how imaging programs and procedures can be used to identify and quantify cellular and tissue morphology as observed in digitised images of tissue samples, as well as characterising staining patterns for the analysis of the expression of key molecular makers in those tissues. By “intelligent algorithms” we mean programs that exploit context-based information and spatial reasoning so it can be used to mechanically reason about image contents, so it can facilitate further analysis on areas of interest that depart from expected ranges of normality and facilitate reaching diagnostic and prognostic conclusions about the tissues analysed.
At present, we would only consider applications from self-funded prospective students with:
- a good biomedical or engineering/computing degree (minimum of a 2:1), with interests in the areas outlined above,
- good command of the English language (written and spoken) as outlined in the postgraduate prospectus,
- competent with computers and data handling (ideally with Java or C language programming skills),
- a source of funding to cover tuition fees and bench fees (note that tuition fees are different for Home and EU students than for International students).
To be considered for this studentship, please send the following documents to
[email protected]:
• A detailed CV, including your nationality and country of birth;
• Names and addresses of two referees;
• A covering letter highlighting your research experience/capabilities;
• Copies of your degree certificates with transcripts;
• Evidence of your proficiency in the English language, if applicable.
Funding Notes
We have a thriving international Researcher community and encourage applications from students of any nationality able to fund their own studies (i.e. through Government scholarship schemes, self-funding), or who wish to apply for their own funding (e.g. Commonwealth Scholarships, Islamic Development Bank International PhD Scholarships, China Scholarship Council, etc).
References
Randell DA, Landini G, Galton A. Discrete mereotopology for spatial reasoning in automated histological image analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 35 (3):568-581, 2013.
Landini G. Fractals in Microscopy. Journal of Microscopy 241, Pt1: 1-8, 2011.
Landini G, Randell DA, Breckon T, Han JW. Morphologic characterization of cell neighborhoods in neoplastic and preneoplastic epithelium. Analytical and Quantitative Cytology & Histology 32:30-38, 2010.
Landini G, Othman IE. Architectural analysis of oral cancer, dysplastic and normal epithelia. Cytometry A 61A:45-55, 2004.
