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12 January 2024
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Story Nonsindiswe Qwabe
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Photo Sonia Small
Since joining the UFS in 2008, Dr Grey Magaiza has worked extensively on approaches that can foster the socio-economic transformation of societies.
“The future should be one where communities can decide on their development agenda and futures. That’s the most important for me.” Dr Grey Magaiza, Deputy Director of the Centre for Gender and Africa Studies (CGAS) and Head of the Community Development programme on the Qwaqwa Campus, is passionate about capacitating communities to be agents of change and advancement. His vision for the future emphasises the empowerment of communities to take charge of their development by actively participating in decision making and the implementation of development projects that can improve their lives.
Since joining the UFS in 2008, Dr Magaiza has worked extensively on approaches that can foster the socio-economic transformation of societies. Over the years, he has crafted his research speciality into one that he is most proud of – being an interdisciplinary scientist immersed in the development of communities.
“I’m in a fortunate position of researching what I like. I say ‘fortunate’, because I’ve taken the time to understand what I’m passionate about, which is the overall field of rural livelihoods and livelihood futures – in short, community development. My research starts from an engaged university, understanding the elements that a university must use to enhance transformation and relevance to its immediate community in terms of development.”
One of the ways he has done this is by looking at social entrepreneurship as a development approach for young people in a rural setting. Through workshops with non-profit and civic organisations in Qwaqwa, Dr Magaiza has been helping these organisations to map out their needs and actively meet them through the involvement and support of external role players.
“We understand that communities are part of the national development agenda, but even that national agenda respects community knowledge and intentions and allows communities to shape their identity. A critical enabler of this is community organising. You bring back the capacity in communities to have dialogues on issues affecting them as spaces for engagement, knowledge exchange, and for people to just talk about their way forward.”
By enabling communities to define their development agenda, they can address their specific needs, challenges, and aspirations, he said. “When I look at livelihood futures, it’s quite an exciting aspect of my work – it’s like looking into a fortune tellers’ globe, because you’re not deciding for communities what they should do, but the communities themselves take those decisions.”
Mathematical methods used to detect and classify breast cancer masses
2016-08-10
Examples of Acho’s breast mass
segmentation identification
Breast cancer is the leading cause of female mortality in developing countries. According to the World Health Organization (WHO), the low survival rates in developing countries are mainly due to the lack of early detection and adequate diagnosis programs.
Seeing the picture more clearly
Susan Acho from the University of the Free State’s Department of Medical Physics, breast cancer research focuses on using mathematical methods to delineate and classify breast masses. Advancements in medical research have led to remarkable progress in breast cancer detection, however, according to Acho, the methods of diagnosis currently available commercially, lack a detailed finesse in accurately identifying the boundaries of breast mass lesions.
Inspiration drawn from pioneer
Drawing inspiration from the Mammography Computer Aided Diagnosis Development and Implementation (CAADI) project, which was the brainchild Prof William Rae, Head of the department of Medical Physics, Acho’s MMedSc thesis titled ‘Segmentation and Quantitative Characterisation of Breast Masses Imaged using Digital Mammography’ investigates classical segmentation algorithms, texture features and classification of breast masses in mammography. It is a rare research topic in South Africa.
Characterisation of breast masses, involves delineating and analysing the breast mass region on a mammogram in order to determine its shape, margin and texture composition. Computer-aided diagnosis (CAD) program detects the outline of the mass lesion, and uses this information together with its texture features to determine the clinical traits of the mass. CAD programs mark suspicious areas for second look or areas on a mammogram that the radiologist might have overlooked. It can act as an independent double reader of a mammogram in institutions where there is a shortage of trained mammogram readers.
Light at the end of the tunnel
Breast cancer is one of the most common malignancies among females in South Africa. “The challenge is being able to apply these mathematical methods in the medical field to help find solutions to specific medical problems, and that’s what I hope my research will do,” she says.
By using mathematics, physics and digital imaging to understand breast masses on mammograms, her research bridges the gap between these fields to provide algorithms which are applicable in medical image interpretation.