Ms. Saumya Kareem, UoA 11, ECS
I joined the University of Westminster in 2007 as a Master’s student after receiving a B.Tech degree in Biomedical Engineering from India. I completed my Master’s in System-on-Chip design for DSP and Communications in 2008 and joined the Applied DSP and VLSI Research Group in October 2009 for PhD. My area of research is mobile phone camera enabled low-power image processing hardware for biomedical applications, specialising in malaria diagnosis in thin blood film images.
I enjoy what I do. My professors are great, supportive and encouraging. The atmosphere in the research lab is excellent with great facilities and ambience. I live in London with my husband and daughter, and with so much to achieve and deal with, I am proud of my decision to choose Westminster for my PhD.
The World Health Organization (WHO) has estimated that malaria causes over 200 million cases of fever annually; in 2010, around 655,000 people died from the disease, most of whom were children under the age of five. Microscopic malaria diagnosis is, by far, considered to be the most effective diagnostic method, but it is highly time-consuming and labour intensive. The accuracy of the system solely depends on the expertise of the microscopist. Automating the process of microscopic diagnosis of malaria parasite in human blood aims to achieve a fast and reliable diagnostic platform without expert intervention for the effective treatment and eradication of the deadly disease.
My research has progressed through the following stages: the first being the identification of the Red Blood Cells (RBC) in which the parasites reside. A novel method called the Annular Ring Ratio (ARR) method has been developed in order to locate the RBCs. Following this, the White Blood Cells (WBC) and infected cells are distinguished using the size, intensity and spatial geometry of the cells. The parasitemia, which is the ratio of infected cells to normal cells and measures the extent of the infection, is calculated at this stage. The next stage is the life stage recognition of the infected cells based on the properties gained over their maturity. The final phase involves species recognition and ultimately deploying the application in a camera-enabled mobile phone platform.
This research is widely acknowledged due to its purpose of study. Once completed, the final product could be used as an effective, low-cost tool for malaria diagnosis as well as identifying the blood components such as RBCs and WBCs.
This research has received a UK-India-Education-and-Research-Initiative (UKIERI) thematic partnership grant in collaboration with Anna University of Science and Technology, Chennai, India.