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25 March 2024
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Story Anthony Mthembu
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Photo Lutendo Mabata
Prof Nompumelelo Zondi, the newly appointed Vice-Dean: Research and Postgraduate Studies in the Faculty of The Humanities at the University of the Free State (UFS).
Prof Nompumelelo Zondi has been appointed as Vice-Dean: Research and Postgraduate Studies in the Faculty of The Humanities at the University of the Free State (UFS). Prof Zondi assumed this new role on 1 March 2024 after serving as the Head of Department for African Languages at the University of Pretoria for seven years. “I consider this appointment as an opportunity of growth and learning more about higher education and the Faculty of The Humanities at large,” she said.
Prof Zondi indicates that part of her role is to spearhead the UFS Vision130 within the Faculty of The Humanities, and to ensure that the faculty assists the institution in becoming research-led, student-centred, and globally impactful.
Motivation for assuming this role
One of the primary reasons that led her to consider this role is sharing the knowledge she acquired as part of the Fulbright South African Research Scholar Programme. As a result of that experience and exposure, which went beyond the Ohio State University, she felt it befitting to implement some of the insights she acquired on a bigger scale. Therefore, even though she was impactful in her previous role, Prof Zondi believes that this is an exceptional and more desirable platform to do so. “I feel that I will have easier access to departments within the faculty, while also encouraging and supporting interdepartmental and faculty collaborations,” she explained.
A significant component of Vision 130
He believes that the elements that make up Vision 130 are interrelated. While she considers research central to Vision 130 – as she begins her journey at the UFS, she feels students deserve to be nurtured to further contribute to the university’s impactful research. Thus, student-centredness is the way to go. “I believe that students must be major role players in this Vision130; we must include them in the interactions and discussions that are part of the university’s strategic plan as well as in decision-making processes,” she said. As such, according to Prof Zondi, the more the faculty and the institution care for the students and involve them in Vision130 and in collaborations, the more research outputs the university will achieve.
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.