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20 December 2020
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Story Thabo Kessah
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Photo Thabo Kessah
Mbuyiselwa Moloi with student volunteers, Keamogetswe Mooketsi (presenter), Tshumelo Phaladi (producer), and Siphamandla Shabangu (SRC member – Social Justice and Universal Access).
The month of October 2020 marked the first anniversary of the Qwaqwa Campus online student radio, Q-Lit. “It has been a rocky road of sleepless nights, tears, and a lot of challenges. However, we have grown from strength to strength. We have made dreams of ordinary students possible. We have influenced change and inspired students to tap into their talents and potential,” said an elated station manager, Mbuyiselwa Moloi.
The station came in handy during the worst lockdown period of the COVID-19 pandemic when it bridged the communication gap between students and the university to integrate teaching and learning into the programming to ensure that no student was left behind. “With all of the regulations and online learning, Q-Lit had to be reinvented. While it was not an easy journey, we have grown more than ever before. Our August 2020 report shows that we have pulled in more than 1 600 listeners, even amid the learning, unlearning, and relearning processes. It was during this month that we also ran a series highlighting strategic offices led by women on campus as part of our Women’s Month celebration,” Mbuyiselwa revealed.
Looking to the future, the station hopes to obtain a full broadcasting licence from the regulatory body, the Independent Communication Authority of South Africa (ICASA), soon.
Mathematical methods used to detect and classify breast cancer masses
2016-08-10
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.