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05 September 2020 | Story Khiba Aubrey Teboho | Photo Supplied
Khiba Aubrey Teboho.

Transformation at the university must be reflected in all dimensions of the institution, such as leadership, governance, and management, student backgrounds such as practical access and academic excellence, equity in staffing, institutional cultures, and inclusive teaching and learning. I acknowledge that this is not an easy task for universities, and that is why I would urge the student population to exercise patience on some of the matters they bring to the institution. However, they should also not be used by the university as a crutch in undertaking its obligation to transform and promote integration, non-discrimination, and inclusivity across all levels –  not only within the university, but also within the local space where the university finds itself, as we know the history of the institution. We have come a long way and there is still more to do, things to change, but we have to give credit where it is due. I still appeal to the institution to do more, because for some students it is the place that will give them the capability to fight poverty, to prosper, to influence change in society, and to change their lives as well as the lives of their families.

The redress of historical inequalities between historically white and historically black universities – it is a challenge for all universities, and we have come a long way to resolve this. With a new culture of students comes a new challenge, such as the funding challenges that poor and middle-income students are constantly facing. These are some of the recurring issues faced by students continually, requiring a solution that does not impoverish the poor even more. Universities must become spaces for transformation, rather than merely being transformed spaces. It is the transformative development through which students come to understand social justice properly, which certifies that students will go on to promote social justice in the wider society. While universities have long been sites of personal growth and transformation for their students, the impact of the transformative power of these places and the important transformational goal of generating graduates who are engaged citizens working for social justice must not be overlooked, particularly in the literature of transformation at the university.

Similarly, what is questioned by the students themselves is the relevance of what is taught at universities, how students are prepared through the knowledge and skills 'transmitted' to them for life in a South African context, and in what sense graduates are prepared to contribute to the advancement of society after the completion of their degrees. It cannot be that in this era we produce graduates who are job seekers, especially considering the status our country is in. This should be carefully considered in the development of the university’s curriculum and in its strategies.

It is only through an epistemic revolution in institutional culture that universities can become spaces that foster the development of civic-minded graduates. We cannot be relegated to just being students when it comes to the issues raised above if transformation is to take place effectively. Students must also understand that we cannot continue to do things as if it were 1976; we need to find other alternative mechanisms to voice our concerns and make an impact. At times change is not easy and it is not comfortable, but we are ready!
God bless South Afrika. Morena boloka setjhaba sa heso.

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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