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08 December 2021 | Story Michelle Nothling | Photo Supplied
Lentsu Nchabeleng
Dr Ntheno Nchabeleng was appointed as the Deputy Director in the Gender and Anti-Discrimination Office within the Unit for Institutional Change and Social Justice.

A total of 10 006 rape cases were reported between April and June 2021. This is according to the latest SA crime statistics for the first quarter of 2021/2022. From a sample of 5 439 of these rape cases, 3 766 of incidents took place in the victim’s home or that of the rapist. A shadow pandemic of gender-based violence against our women and children is raging in South Africa.

It is within this global and local context that the Gender and Anti-Discrimination Office (GEADO) at the university is making inroads into supporting survivors of gender-based violence (GBV) and changing gender stereotypes.

GEADO in focus

GEADO is situated within the Unit for Institutional Change and Social Justice on the Bloemfontein Campus. It is mandated to deal with incidents of unfair discrimination and GBV as it relates to the UFS community, and to conduct advocacy and training in these areas. Deputy Director of GEADO, Dr Ntheno Nchabeleng, explains that “through high-impact practices and interventions, the Office works to systematically reduce case attrition to ensure that all reports and cases follow procedurally just processes”.

GEADO has been established at all the UFS campuses with well-trained and fully equipped Senior Gender Officers leading each. Geraldine Langau—supported by research assistant Delisile Mngadi—is managing the office at the Bloemfontein Campus, Chelepe Mocwana the Qwaqwa Campus, and Sivuyisiwe Magayana oversees the South Campus office.

Addressing gender-based violence

Prevention and response to GBV are at the core of GEADO’s work. With our country wracked by sexual violence and femicide, “it has become a nightmare to be a woman in South Africa”, Dr Nchabeleng says.

Its preventative efforts focus on the underlying causes of GBV to transform patriarchal notions, misogynistic norms, power imbalances, and toxic gender stereotypes. Fostering collaboration with various strategic partners to strengthen its impact, GEADO recently started working with Amnesty International Sub-Saharan Africa and Amnesty International Latin America to spread awareness on various forms of violence experienced by vulnerable populations. GEADO has also partnered with other local stakeholders in an effort to eradicate GBV through programming that includes awareness campaigns, online mobilisation, training, and webinars.

Becoming part of the solution

“Become change agents,” Dr Nchabeleng urges. One way to start shifting attitudes and mindsets is to change the way we speak. Examples would be to refrain from sexist and discriminatory language and phrases that undermine and degrade our women. Gendered name-calling generally depicts women and girls as inferior and less than fully human. Another area of concern is the way young people — especially young men — engage in disparaging conversations about women on social media platforms. This behaviour needs to cease. As a society, we also need to stop victim blaming, stop normalising rape culture, and stop entertaining sexual violence jokes,” Dr Nchabeleng says.

These changes start with each of us.

Incidents of GBV and discrimination can be reported to GEADO at:
Bloemfontein Campus: +27 51 401 3982
South Campus: +27 51 401 7544
Qwaqwa Campus: +27 58 718 5431

Sexual Assault Response Team (SART):
www.ufs.ac.za/sart 
Toll-free number +27 80 020 4682

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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