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2024 Elections: What the future holds after 29 May

02 May 2024 | Story Dr Nitha Ramnath | Photo right

2024 UFS Thought-Leader Webinar Series

PRESENTS

a webinar titled

2024 Elections: Promises, Perils, and Delivery: What the Future Holds After 29 May 2024?

The University of the Free State (UFS) is pleased to present its first webinar for the year, titled 2024 Elections: Promises, Perils, and Delivery: What the Future Holds After 29 May 2024? – which is part of the 2024 Thought-Leader Webinar Series. As a public higher-education institution in South Africa with a responsibility to contribute to public discourse, the university will be presenting the webinar as part of the UFS Thought-Leader Series, which is in its sixth consecutive year. The aim of the webinar series is to discuss issues facing South Africa by engaging experts at the university and in South Africa.

Webinar presented on 23 May 2024

On 29 May 2024, South Africans will go to the polls. This election is considered by South Africans as significant and much needed since the end of apartheid in 1994. South Africa is plagued by record power cuts, poor service delivery, and high levels of unemployment, with drastic effects on businesses and the local economy. Coinciding with the celebration of 30 years of freedom and democracy, this seventh democratic election is a turning point for South Africa to determine the desired future for all South Africans.

Date: Thursday 23 May 2024

Time: 12:30-14:00

RSVP: Click to view document HERE no later than 22 May 2024.

Some of the topics discussed by leading experts in 2023 included, among others, Threats to South Africa’s stability and security challenges; The need for a global and regional plan / approach to respond to the consequences of the Russia-Ukraine war; and Student protest action, politics, and higher education.

Facilitator:

Prof Francis Petersen

Vice-Chancellor and Principal, UFS

Panellists:

Prof Bonang Mohale

Chancellor, UFS

Dr Ebrahim Harvey

Political writer and commentator

Bios of speakers:

Prof Bonang Mohale

Prof Bonang Mohale is the Chancellor of the University of the Free State, former President of Business Unity South Africa (BUSA), Professor of Practice in the Johannesburg Business School (JBS) College of Business and Economics, and Chairman of two listed entities – the Bidvest Group Limited and ArcelorMittal, as well as SBV Services and Swiss Re Corporate Solutions! He is a member of the Community of Chairpersons (CoC) of the World Economic Forum and author of two best-selling books, Lift As You Rise and Behold The Turtle! He has been included in the Reputation Poll International’s (RPI) 2023 list of the ‘100 Most Reputable Africans’. The selection criteria are integrity, reputation, transparency, visibility, and impact. He is the recipient of the 2023 ME-Vision Academy’s ‘Exclusive Recognition in Successful Leadership’ Award for consistently leading self successfully, consistently leading people successfully, successfully leading as a senior executive and CEO, successfully leading society in various impactful roles, and his contribution to mentoring and inspiring future successful leaders.

Dr Ebrahim Harvey

Dr Ebrahim Harvey is a political writer, analyst, commentator, former Cosatu trade unionist, and Mail & Guardian columnist. He is currently a News24 columnist. He also wrote the authorised biography of former president, Kgalema Motlanthe (2012), and The Great Pretenders: Race and Class under ANC Rule (2021), which won the 2022 SA Literary Award for Non-Fiction. He holds a master’s degree in Public and Development Management and a PhD degree in Sociology, both from the University of the Witwatersrand.

News Archive

Mathematical methods used to detect and classify breast cancer masses

2016-08-10

Description: Breast lesions Tags: Breast lesions

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.

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