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28 May 2024 | Story Jacky Tshokwe | Photo supplied
Reading Culture
The University of the Free State Faculty of Humanities and the Library Information Services proudly established a brand-new school library at Kagisano Combined School on 14 May 2024.

In a bid to cultivate a culture of reading within the community and bolster the University of the Free State's (UFS) Vision 130, the Faculty of The Humanities has embarked on a transformative journey of collaboration with the Library Information Services (LIS). This partnership symbolises a commitment to not only academic excellence, but also social responsibility, aiming to make a tangible difference in the lives of those within our community.

On 14 May, the Dean’s office – in synergy with LIS and the Department of Plant Sciences – undertook a meaningful venture at Kagisano Combined School in Ikgomotseng to establish a school library, making it an engaging and welcoming space for learners.

Led by Dr Dimitri Veldkornet and supported by four dedicated PhD candidates, the Department of Plant Sciences has made a remarkable impact by enhancing the library's surroundings with indigenous flowers. Beyond mere beautification, this initiative also served as an educational opportunity, as five learners from the school were trained to care for these plants, fostering a sense of ownership and environmental stewardship.

Colleagues from LIS meticulously and simultaneously organised the library space, ensuring that reading materials were properly catalogued and shelved for easy access. In addition, LIS generously donated furniture, including shelves, tables, and chairs, to create an inviting environment conducive to learning and exploration.

The collaborative effort extended beyond academic circles, as the community of Ikgomotseng and Letsatsi Trust demonstrated remarkable hospitality by combining resources to provide refreshments for UFS colleagues and community members involved in the initiative. This gesture exemplifies the power of collective action and highlights the interconnectedness between the university and its surrounding communities.

By revitalising the school library and fostering a culture of reading, this partnership exemplifies the core values of social responsibility and community engagement espoused by the UFS. Moreover, it underscores the university's commitment to Vision 130, which envisions a future where education transcends the confines of academia to positively impact society at large.

As we continue to forge ahead, let us remember that true progress is measured not only by academic achievements, but also by the meaningful contributions we make to the communities we serve. Together, through collaboration and compassion, we can create a brighter, more inclusive future for all. 

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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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