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17 June 2020
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Story Dr WP Wahl
The Division of Student Affairs (DSA) prioritises innovation to meet the challenges of food insecurity and malnutrition among students. To this end, several student volunteers and student governance structures are collaborating with the DSA on various initiatives.
During 2019, various conversations were held about the possibility of creating a health-promoting food environment at the UFS where students and staff are well informed and empowered to take appropriate action regarding their food and nutritional needs. These conversations resulted in an institutional strategy to address the food environment at the UFS. Student representatives serve on a technical committee that directs the implementation of this strategy. In this regard, several initiatives have already been launched.
Students from residences and other student communities have planted vegetable gardens on the Bloemfontein Campus with the assistance of KovsieACT and the Faculty of Natural and Agricultural Sciences. Students and staff are already harvesting and distributing vegetables to needy students every week. Measurements were put in place to continue this during the COVID-19 period. The following vegetables were planted: spinach, cabbage, beetroot, broccoli, cauliflower, and carrots.
Food parcels, donated by Tiger Brands and Gift of the Givers, are continuously handed out by DSA staff and student volunteers. In this regard, 540 food parcels have already been handed out on the Bloemfontein Campus during the COVID-19 period alone. During the same time, 117 students received food parcels on the Qwaqwa Campus. The innovation of this food parcel project rests on the fact that business, NPOs, UFS students, and DSA staff are collaborating to address food insecurity and malnutrition.
More collaborative initiatives will be implemented over the next 12 months. The DSA staff and students are already working with the Department of Dietetics and Consumer Sciences to create information packages about the preparation of low-budget nutritious meals.
Related article:
Vegetable tunnels established to continue the fight against food insecurity
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.