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17 March 2021 | Story Karen Venter
As illustrated in the infographic, the input from engaged activities delivered by the UFS resulted in 285 engaged-activity outputs, of which the majority constituted engaged citizenship, followed by engaged research, and then engaged learning and teaching.


View infographic here

At the University of the Free State (UFS), engaged scholarship activities are guided by the vision of being a research-led, student-centred, and regionally relevant university, focused on development and social justice.

For enactment of this vision, the UFS invests physical resources and funding, as well as staff and student hours to contribute to nation building. 

Demonstrating the heart of strategic partnerships

Engaged scholarship demonstrates the heart of strategic partnerships, where agreements are grounded in shared goals, designed and agreed upon in unity for socio-economic renewal to improve people’s living conditions, contributing to societal well-being. It links the best of the research and teaching skills of staff and students to specific needs of the community, including civil society, the private sector, government, non-governmental organisations, and enterprises. 

Democratic knowledge co-creation emerges from engaged learning and teaching, engaged research, and engaged citizenship through interaction between the institution, its staff and students, and the community. 

The curriculum, engaged research efforts, engaged learning and teaching, and graduate attributes are all enriched through collaborative and reciprocal learning activities. As illustrated in the infographic, the input from engaged activities delivered by the UFS resulted in 285 engaged-activity outputs, of which the majority constituted engaged citizenship, followed by engaged research, and then engaged learning and teaching. 

Deep understanding of socio-economic and environmental challenges

Our students participate in community-engaged service-learning, leading to knowledge acquisition and a deep understanding of socio-economic and environmental challenges in mutual solidarity with the community. Service-learning also gives rise to the acceptance and understanding of diverse cultures and races and advances the ability to interact meaningfully with diverse people from different backgrounds. 

Community-engaged learning increases awareness of own biases and stereotypes along the dimensions of race, ethnicity, culture, gender, sexual orientation, socio-economic status, age, physical abilities, religious beliefs, political beliefs, or other ideologies. By transcending their own comfort zones, combined with collaborative learning with diverse groups, students can gain greater appreciation of the strengths and capacities of diverse groups in the community. 

The UFS invests physical resources and funding, as well as staff and student hours to contribute to nation building. – Karen Venter

Engaged scholarship also embraces the inculcation of citizenship and the social responsibility of the UFS to society by giving effect to one of the key ‘public good’ dimensions of the UFS. 

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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