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iCAN Vol. 4: A Tapestry of Voices

10 October 2024

The Centre for Teaching and Learning recently unveiled the fourth volume of the Initiative for African Narratives (iCAN), a vibrant celebration of diverse voices at the University of the Free State (UFS). This latest anthology features 48 stories presented in 10 of South Africa’s official languages: Afrikaans, English, isiNdebele, isiXhosa, isiZulu, Sesotho, Sepedi, siSwati, Tshivenda and Xitsonga. Contributors include Kovsie writers from all three UFS campuses, reflecting the university’s rich linguistic and cultural diversity.

“This initiative forms part of the university’s commitment to promoting multilingualism while providing a platform for a wide array of narratives,” said Dr Peet van Aardt, iCAN Coordinator. “Every student at the university has stories to tell – whether drawn from their personal experiences or shaped by their imagination.”

The launch, held on the Bloemfontein Campus, attracted around 150 students. Attendees were treated to musical performances by the Conlaures Choir, conducted by Omphemetse Phaswana, and a captivating saxophone solo by Thabo Dlamini from the Odeion School of Music. Representatives from the Academy for Multilingualism and African Languages Press were also present, underscoring the event’s focus on the intersection of language and expression.

This year's anthology, iCAN Vol. 4, is the ninth publication under the iCAN initiative in the past seven years. In addition to these collaborative anthologies, iCAN has also published several standalone works by solo student authors. Coordinated by senior student writer Siphila Dlamini, this volume showcases some of the finest writing talent across the UFS campuses.

Student of the year

Shortly after the iCAN launch, the Office of the Executive Dean of Student Affairs announced that Siphila Dlamini had been awarded the prestigious EDSA Student of the Year 2024 title. His contributions to student success and well-being were lauded as being aligned with the university’s strategic objectives.

Currently completing his Postgraduate Diploma in Governance and Political Transformation, Siphila plans to pursue a master’s degree next year. Reflecting on the award, he said, “This recognition, stemming from my work with iCAN, is a humbling reminder of the power of storytelling to transcend boundaries. It reaffirms my belief that by amplifying diverse voices and fostering creativity, we can spark change, inspire growth, and leave an indelible mark on our collective narrative.”

Siphila’s accolade marks the second consecutive win for an iCAN writer. Last year, the award was bestowed upon Tlotlisang David Mhlambiso from the Faculty of Education, further highlighting the initiative’s role in nurturing outstanding talent.

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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