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30 May 2025
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Story Prof Mikateko Mathebula
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Photo Supplied
Pictured (from left to right): Prof Faith Mkwananzi, Dr Kapambwe Mwelwa, Prof Lochner Marais, Prof Chikumbutso Manthalu, and Prof Mikateko Mathebula.
Through collaborative agreements with the University of Malawi and the University of Zambia, the University of the Free State (UFS) has established the Research Alliance for Higher Education in Africa (RAHEdA), a dynamic initiative aimed at enhancing research capacity and partnerships within Sub-Saharan Africa.
The collaborative agreements align with the UFS’s Vision 130 strategy in relation to internationalisation, emphasising the important role that intra-African mobility visits play in establishing relationships with universities on the continent. It also fosters knowledge exchange and engagement and allows for careful planning and strategy meetings.
“During these discussions, an ambitious but feasible roadmap was laid out for the next three to five years,” Prof Mkwananzi said. “These activities include online workshops for staff and postgraduate students at all partner institutions, and a new webinar series that focuses on profiling, advancing, and celebrating thought leaders, higher education scholars, and scholarship in Africa.”
The inaugural webinar was held on 21 May 2025. Speaker Prof Siseko Kumalo, Associate Professor at the University of Johannesburg’s Ali Mazrui Centre for Higher Education Studies, spoke on ‘Orality as the Bulwark of the Humanities?’, set the bar high for the webinar series through his compelling and original response to this timely question, as scholars around the world contemplate appropriate responses to the rise and influence of artificial intelligence in higher education teaching, learning, and assessment.
Funding to support RAHEdA has been generously provided by Prof Melanie Walker, Distinguished Professor and SARChI Chair in Higher Education and Human Development.
• For information on how to get involved and for updates on RAHEdA, please contact Prof Mikateko Mathebula at MathebulaM@ufs.ac.za
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.