Latest News Archive

Please select Category, Year, and then Month to display items
Previous Archive
22 September 2021 | Story Michelle Nöthling | Photo Supplied
Lerato Sheila Thamahane.

Lerato Thamahane may be able to speak and understand all nine of South Africa’s official African languages, but it is a tenth language she is devoting her life to: South African Sign Language (SASL).

With nearly ten years’ experience as a SASL interpreter in several settings – ranging from the medical and mental-health fields to that of conferences and Deafblind interpreting – Lerato is living her life’s purpose. “I regard myself as a member of the Deaf community and a servant at the same time.”

Lerato lives by the principle that the more perspectives she gains on the world, the better service as an interpreter she can provide. This is also part of the reason why Lerato decided to take on the role of student again to study BA Language Practice to provide her with an even broader perspective on the field. 

But why does Lerato feel so strongly about SASL? It is only through Sign Language, Lerato explains, that one can bridge the divide between the world of the hearing and that of the Deaf. “SASL is the only way for the minority Deaf group to receive and transfer information,” Lerato emphasises. “Deaf people cannot communicate in any other way.” Now, consider for a moment the plight of a Deaf child in South Africa. To receive education in SASL, most Deaf children have to move far away from home at a very young age in order to attend a school for the Deaf. For many years, schools for the Deaf did not include other languages as subjects, which prevented Deaf school-leavers from entering higher education. Although this situation has largely changed, Deaf students are still fighting an uphill battle when entering higher education institutions where prejudice and ignorance still persist. This is where the work of the Centre for Universal Access and Disability Support (CUADS) and the Department of South African Sign Language (SASL) and Deaf Studies makes such a crucial difference.

“I firmly believe,” Lerato says, “that only Sign Language can open opportunities for all groups of the Deaf community – from Deaf children to adults, and from the uneducated to the most educated Deaf people.” It is for this reason, Lerato argues, that our constitution needs to recognise SASL in order to give Deaf people full and equal access to information, to education, and ultimately, to all the opportunities South Africa has to offer.


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