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18 October 2019 | Story Ruan Bruwer | Photo Getty Images
Jaco Peyper
Jaco Peyper, former Kovsie, will handle a quarter-final match at the Rugby World Cup. It will also be his 50th test match.

With the appointment of Jaco Peyper as referee there will be Kovsie alumni among the referees, players and coaches in the quarter-finals of the 2019 Rugby World Cup in Japan on 20 October.

Lappies Labuschagné will start on the flank for Japan in their clash against the Springboks on Sunday. Labuschagné, a former Shimla captain, is second on the list for tackles made in the tournament thus far.
In the Springbok camp there are former University of the Free State (UFS) students in Rassie Erasmus (head coach) and Jacques Nienaber (defence coach).

UFS alumnus Jaco Peyper has been entrusted with the whistle in Sunday’s other quarter-final between Wales and France. It will be a memorable match for Peyper as it will be his 50th test appearance as the 31st man on the field – making him only the third South African to achieve this feat.

Peyper, who is the only South African among the 12 referees at the tournament, made his World Cup debut in 2015 when he officiated the opening match. In total he has handled six World Cup encounters. 

His illustrious career has seen him become only the fourth referee in history to officiate in 100 Super Rugby matches earlier in the year, in which he also handled the final (his fourth Super Rugby final). Peyper scooped the SA Referee of the Year award in 2018 for a third time, a year in which he took charge of his fourth Currie Cup Final.

“The fact that he is only the third South African referee to take charge of 50 tests indicates what a special achievement this is. It takes years of hard work and dedication to reach this level as a referee, and to maintain this standard year-in and year-out is even more challenging as it requires one to produce effective performances consistently,” said Jurie Roux, the CEO of SA Rugby.

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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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