Latest News Archive

Please select Category, Year, and then Month to display items
Previous Archive
12 September 2019 | Story Valentino Ndaba | Photo Charl Devenish
Arbor tree plant
To celebrate National Arbor Week the University of the Free State has embarked on a drive to plant 150 trees during the month of September

If you’ve wondered whether Arbor Month was important, you only have to look at the destruction and long-term damage that deforestation causes to the environment and the world’s inhabitants. To observe National Arbor Month, the University of the Free State’s has (UFS) kick-started a drive to plant 150 trees during the month of September.

To launch this initiative, the Rector and Vice-Chancellor, Prof Francis Petersen, alongside members of the rectorate, assisted the University Estates team in planting the first 10 of 100 trees at the Bloemfontein Campus on Wednesday 4 September 2019. A total of 50 trees will be planted on the Qwaqwa Campus.

Towards a sustainable future

“We have gone through periods of drought in the Free State that have severely impacted not only the plants but the trees on our campuses. The idea is to emphasise sustainability, and as a university, we believe that sustainability is important. As an education institution, we have to look at the generations that are still to come to our campuses,” said Prof Petersen.

He urged the Kovsie community to ensure that all practices across the campuses are linked to global standards of sustainability. “As we develop over the next couple of months and years, we will get much closer alignment between what we are doing as a university and the Sustainable Development Goals.

Drought-resistant man-made forests

Clusters of mini forests across the campuses will be created with a variety of trees including the karee, white karee, white stinkwood, and wild olive. These indigenous trees can adapt well to different soils including those that are poorly drained.

Celebrating Arbor Week

This year’s campaign was held under the theme Forests and Sustainable Cities. As part of the celebration, University Estates made a commitment to the environment by embarking on the green initiative which includes other project such as the upgrade of Red Square on the Bloemfontein Campus.

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.

We use cookies to make interactions with our websites and services easy and meaningful. To better understand how they are used, read more about the UFS cookie policy. By continuing to use this site you are giving us your consent to do this.

Accept