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08 August 2023
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Story EDZANI NEPHALELA
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Photo EDZANI NEPHALELA
Mbulelo Aven Jafta, Xhariep Municipality Corporate Services Director, and Dr Engela van Staden, Deputy Vice-Chancellor: Academic at the UFS, sign a memorandum of understanding to enrich various communities in the Xhariep Municipality areas through leadership training.
The University of the Free State (UFS) has signed a memorandum of understanding with the South African Local Government Association (SALGA) and the Xhariep Municipality that is aimed at positively impacting communities through strategic partnerships. The organisations plan for their collaboration to make a significant difference by training 35 of their employees via the UFS Business School – 15 will undertake the Foundation Skills Short Learning Programme, and 20 the Bachelor’s degree in Management Leadership.
This joint effort will equip these employees with essential skills and knowledge and empower them to carry out their responsibilities efficiently and effectively. Rooted in the UFS’s Vision 130, this initiative fosters positive change within the community by enhancing social justice and innovation.
Dr Engela van Staden, Deputy Vice-Chancellor: Academic at the UFS, emphasised the university's dedication to human resource development and empowering individuals. “We were very excited when we got this engagement with you, and I hope it will be fruitful for you, because that’s the intention. We are also reaching out to other municipalities because we are doing it for our country, and the sooner we do it, the better the services you will deliver to people.”
Xhariep Municipality expressed gratitude for the collaboration, recognising its significance in empowering its employees. Mbulelo Aven Jafta, Corporate Services Director at the municipality, thanked the university for accepting the partnership. “As a municipality, we are interested in capacitating our employees to perform their duties optimally. It is through these partnerships that we reach our intended targets. This is the first two projects, and many more will be coming as our partnership progresses, and we intend to use this opportunity to the best of our abilities.”
Jafta said that such partnerships encourage a more interconnected and interdependent world. “As organisations work towards common goals, they create a ripple effect that can lead to a brighter and more promising future and play a vital role in shaping a positive and sustainable future.”
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.