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01 June 2023
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Story Nicole Bongo
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Photo Supplied
University of the Free State students participating in one of the many projects coordinated by the Engaged Scholarship Office.
To help make a change and push for sustainable development, the University of the Free State Division of Student Affairs works with communities around Bloemfontein fostering a culture of creating sustainable solutions.
Gernus Terblanche, Kovsie Support Services and Assistant Researcher in the Division says, ‘it is important for the university to be actively involved in the community as it makes up such a large portion of the Bloemfontein and students also
represent many different communities on and off- campus.’
Terblanche said: “As an educational institution it is vital for the UFS to support and guide students towards creating innovative solutions; both local and globally. Our experience is that students often come up with real solutions that can
make a real impact in the lives of real people – and it would be crucial to support such initiatives.”
The office has worked with BloemShelter, VermiVillage, GAP Equip, National Hospital and as part of the programmes of 2022 also with Lighuis, Talita Cumi, ROC Kids and the Universitas Neighborhood association. “We are also very fortunate to have,
Shanen Emam, Miss Free State 2023 as one of our students that are involved with our programmes,” added Terblanche.
One of the students involved is Prince Sijane, Bloemfontein Campus Student Representative Council member responsible for Civic and Social Responsibility when asked why student participation is important, he said, “By actively participating in
initiatives that address social issues or promote community well-being, students become more aware of the challenges faced by society.”
Tereblanche said: “The produce of these gardens addresses hunger and malnutrition amongst students on campus. KovsieACT also facilitates an eco-vehicle project during which student teams learn how to build electric vehicles powered by solar charging
stations. This project is aimed at developing skills appropriate to the 4th Industrial Revolution and sustainable resources development including clean and green energy.”
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.