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26 March 2018 Photo Pixabay
Back to the drawing board to save water
We’ve managed to damage nature’s ‘filter’ with air, ocean, and soil pollution, and by destroying wetlands.

Dr Cindé Greyling, a University of the Free State (UFS) DiMTEC (Disaster Management Training and Education Centre for Africa) alumni, studied drought mitigation with a strong focus on communicating important water-saving information. 

Can we run out of water?
Yes, and no, says Dr Greyling. “To our knowledge, water is not ‘leaking’ through our atmosphere. We have what we have, but that doesn’t mean we will have enough clean, fresh water forever. Nature has a magnificent way of purifying water through the water cycle. We, on the other hand, must use a lot of money and energy to purify water. Also, we’ve managed to damage nature’s ‘filter’ with air, ocean, and soil pollution, and by destroying wetlands. The other problem is a simple supply and demand scenario. More people will need more water, but not only that, population growth calls for industry development and increased food supplies – all of which require more water.”    

A war over water
Besides some Hollywood impressions, it is difficult to imagine a war over water, but it is possible. “Some experts are convinced that we are heading there, and others claim that such tensions already exist. Personally, I don’t favour these kinds of shock tactics (or truths) – social research has shown us that it rarely leads to behavioural changes. We can learn a lot from what was has been done in Cape Town. Although we all think people were bombarded with ‘Day-Zero’-scares, they were actually encouraged to adapt their behaviour with a communication campaign that hardly ever used the term ‘Day-Zero’. This approach mobilised citizens to reach record lows of water usage.” 

Adapt a new normal
Dr Greyling encourages the “new normal” set in motion by Capetonians. “Water consciousness is needed, even when the rain comes again. We’ve taken water for granted for too long. As consumers, we have the power to turn this situation around – drop for drop. Be aware about the amount of water you use, how you use it, and for what. Keep in mind that any wastage and pollution (of ‘dry’ things) also wastes and pollutes water. Generally, we need to behave better regarding consumption.”  

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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