Latest News Archive

Please select Category, Year, and then Month to display items

Opinion: KwaZulu-Natal floods: Each one help one

26 April 2022 | Story Dr Qinisani Qwabe

South Africa recently witnessed a catastrophic natural disaster that resulted in the loss of life, livelihoods, and infrastructural damage. This occurred in KwaZulu-Natal where hundreds of people lost their lives as a result of extensive flooding and mudslides. President Cyril Ramaphosa declared a national state of disaster to which we should all respond. Specific reference was made to the public and private sectors, as well as civil society.

While I applaud the various stakeholders that have extended a helping hand, my heart bleeds for the vulnerable groups whose voices remain unheard, even under normal circumstances. One cannot help but wonder if aid will reach the isolated regions that suffered the adverse effects of these heavy rains, or if all developmental efforts will be prioritised to certain economic hubs of the province such as the eThekwini Metro and the capital, uMgungundlovu.

KwaZulu-Natal is among the poorest provinces in the country. Corroborating this claim is a report that was released by Statistics South Africa earlier this year which reveals that about 52% of the province’s population are considered to be ‘poor’,and live at the lower end of the poverty line.

Drawing from my experiences of the rural communities of KwaZulu-Natal with whom I have worked, many suffer from the triple challenge of poverty, inequality, and unemployment, and rely on agriculture for their livelihood and to put food on the table. Their supplementary income is obtained from government support grants. The graphic scenes that have been shown on the media illustrate the devastating effects of the heavy rains in regions within the agricultural sector. Fields have been washed away, crops and livestock have been lost. This is happening when the province is still trying to resuscitate its economy after the widespread looting that took place in July last year, which had a calamitous effect on businesses and livelihoods.

While this is an injury mainly for the people of KwaZulu-Natal, it is my wish that we all join hands in contributing towards the restoration of livelihoods. In agreement with the president’s assertion, we can all play a part in rebuilding the province. This includes institutions of higher learning, particularly the Community Engagement Directorates whose mandate is to drive socioeconomic development to external communities.

Related article: Opinion: KZN floods expose significant socio-economic and environmental vulnerabilities

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.

Back

Economic and Management Sciences

Education

Health Sciences

The Humanities

Law

Natural and Agricultural Sciences

Theology and Religion

Open Distance Learning

Business School

We use cookies to make interactions with our websites and services easy and meaningful. To better understand how they are used, read more about the UFS cookie policy. By continuing to use this site you are giving us your consent to do this.

Accept