Latest News Archive

Please select Category, Year, and then Month to display items
Previous Archive
10 March 2020 | Story Rulanzen Martin | Photo Victor Sguassero (kykNET)
Chris Vorster
Chris was on stage in 'Die Hart Verklap' at the Toyota US Woordfees in Stellenbosch recently.

“Difficult and very strange,” is how Chris Vorster, veteran actor and Drama lecturer at the University of the Free State (UFS) describes his role as Bas Koorts in the supernatural thriller Die Spreeus

For Chris, the biggest challenge during the filming of Die Spreeus was to work in front of a green screen. “You never see the monsters and things attacking you, it is only added later on during the editing process,” he said. Therefore, he and his co-actors were expected to use their own imagination “to be frightened, and to duck and dive from something that does not exist.” 

This Afrikaans thriller series has recently been nominated in five categories of the South African Film and Television Awards, including Best Television Drama, Best Cinematography, and Original Sound and Sound Editing. 

Chris was also nominated for a Fiësta award in 2019 for his one-man performance in the theatre production, Die Hart verklap. “It is fantastic to still be recognised for my work,” he said, “but I also have to give recognition to Dion van Niekerk, because without a good director, any actor will be lost.” Van Niekerk also lectures Drama at the UFS.

Being a lecturer broadens his knowledge 

Chris joined the UFS Department of Drama and Theatre Arts in 2015 as lecturer in the programme for Film en Visual Media. “Everything I learn in the industry I apply as lecturer, and research and teaching feed more knowledge on acting, directing, and especially writing,” he said. After five years, being involved with the UFS Department of Drama is still exciting to him. “This is where both lecturers and students get encouraged to do more than just breathing.” 

With his busy schedule of teaching and acting, it remains important to him that South Africans are still able to tell stories – “in any language”. He considers it a privilege for anyone to work in their mother tongue. This is also why the symbiosis between his work as actor and lecturer is so appealing.

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.

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