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03 September 2018 Photo Dion Van Niekerk
Drama department gets moving with physical theatre
Elements of physical theatre incorporated in this year’s production of Tok-Tok. Pictures are Charl Henning and Erick Strydom

Dion van Niekerk, a lecturer at the Department of Drama and Theatre Arts at the University of the Free State (UFS), had the unique experience of attending a seven-day Physical Theatre summer school at Retzhof Castle in Austria. Also on the course were Charl Henning, a master’s student, and Erick Strydom, a former student, 

“We learned about the physicality of theatre, which means training for nine hours a day,” Van Niekerk said. “We researched the connection between physical action and voice, gesture, movement, dance and word.” 

New approach to teaching aspiring actors

Many theatres are doing away with sets and costumes and focus mainly on the actors’ bodies. You will find it in mime, clowning and dance. It is a way of telling stories by using only body language. “It gave me insight into what is happening in theatres across Europe,” Van Niekerk said. It also provided the opportunity to benchmark against the rest of the world.

Van Niekerk brought back a new approach with which to train students in the department, and a new way of working with actors. “The relevant training is to make theatre accessible to everyone,” he added. Without a word being said on stage, theatre will be able to accommodate hearing-impaired audiences and cut across all languages.

Physical theatre will do away with barriers

“Physical theatre can accommodate everyone. It will cross boundaries as it will become a common entertainment language,” Van Niekerk said. Putting emphasis on physical theatre was also a way to see what the rest of the world was doing in terms of theatre and training.

Van Niekerk and his team incorporated what they had learnt in Austria into a play called  Tok-Tok, which was performed at the Free State Arts Festival earlier this year.  The summer school took place from 29 June 2018 to 5 July 2018.

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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