About the Project
Malaria is a treatable infectious disease caused by protozoan parasite (genus Plasmodium). According to the latest World Health Organisation (WHO) assessment (2015) from 104 malaria endemic countries, there are about 3.2 billion people at risk and an estimated 660,000 deaths annually. These figures could be hugely reduced with early diagnosis. This proposal aims to develop a fast and efficient plasmodium species recognition system that can be deployed in mobile devices. It has the potential to be used, both as a standalone object identification tool and in conjunction with a complete malaria diagnosis system. The research is of interdisciplinary nature and requires pathology laboratory facilities for slide preparation including storage, processing and staining coupled with engineering aspects for image acquisition and processing. Since each of the 4 plasmodium species exhibit distinctive characteristics, an identification strategy for each species needs to be developed using morphological image processing, feature classification and pattern recognition algorithms. The research also aims to achieve a number of secondary goals including fast, autonomous identification of the zone of morphology, field selection based on image quality and overlapped cell elimination in the selected zone of morphology. The project being unique, novel and cross-disciplinary, has the ability to generate quality publications in both engineering and medical fields. Previous work done within the University in the same field has generated excellent publications in IEEE conferences and healthcare journals. The proposed project will build on this earlier work and significantly extend its usefulness in the field. This research has the potential for a huge impact on healthcare in malaria-endemic regions both for diagnosis of individual cases and epidemiological surveys as well as being a serious candidate for commercialisation as a powerful diagnostic tool.
Funding Notes
A number of full-time Studentships are available, to candidates with Home fee status in the Faculty of Science and Technology starting in September 2017.
The Studentships on offer are:
• Full Studentship - £16,000 annual stipend and fee waiver
• Fee Studentship – Home fee waiver
References
[1] S.Kareem, I .Kale, R.C.S Morling, “Automated Malaria Parasite Detection in Thin Blood Films: - A Hybrid Illumination and Color Constancy Insensitive, Morphological Approach “, IEEE Asia Pacific Circuits and Systems Conference -APCCAS 2012, Taiwan.
[2] S.Kareem, I .Kale, R.C.S Morling,”A Novel Fully Automated Malaria Diagnostic Tool Using Thin Blood Films” IEEE Pan American Health Care Exchanges -PAHCE2013, Madellin, Columbia.
[3] C.Dallet, S.Kareem, I. Kale, “Mobile Malaria Diagnosis: Real time mobile diagnostic application on Android using Java” published at the IEEE International Symposium for Circuits and Systems- ISCAS 2014, Melbourne, Australia.
[4] S.K Reni, I .Kale, R.C.S Morling,“Analysis of Thin Blood Images for Automated Malaria Diagnosis” IEEE International Conference on E-Health and Bioengineering - EHB 2015, Iasi, Romania.