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22 July 2021 | Story Ruan Bruwer | Photo Roger Sedres
Can Wayde van Niekerk repeat his amazing feat from the 2016 Olympics – now five years later – at the next Games?

It is a year later, but the Tokyo 2020 Olympics finally started on Friday, 23 July 2021. In team South Africa, a couple of the athletes and management, many of them medal contenders, call themselves Kovsies.

From 1 August, the progress of the country’s golden boy, Wayde van Niekerk, will be closely followed when he tries to hold on to the title as Olympic 400 m champion – he is still the world record holder (set at the 2016 Games). The final of the 400 m is scheduled for 5 August.

One of only five female athletes in the South African team, Gerda Steyn will compete in the marathon on 7 August. This is her first time at the Olympics. 

She is in red-hot form. In April, she broke a 25-year record in Italy when she ran the fastest-ever marathon by a South African woman, finishing in 2:25:28. She is the defending Comrades and Two Oceans champ.

Protea hockey player, Nicole Erasmus, will become a fourth-generation Olympic contender in her family. Her mother, Lynne Walraven (née Tasker) was a Zimbabwean swimmer, her great-uncle, Anthony Tasker, was a member of the South African rowing team, and her great-great-uncle, Frank Rushton, was a South African hurdles athlete. 

From 26 to 28 July, the South African sevens rugby team, with former Shimlas Chris Dry as a team member and Neil Powell as head coach, will aim to improve on their bronze medal achieved in 2016. Powell was also the head coach at the time, and another former Kovsie, Philip Snyman, captained the Blitzboks.

Kate Murray (formerly Roberts), head coach and high-performance manager of Triathlon South Africa, will act as the SA triathlon coach. She is a double Olympic participant, having raced for South Africa at the 2008 and 2012 Olympic Games.

 


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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