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01 October 2019
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Story Prof Francis Petersen
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Photo Pixabay
During October, the national focus is on mental health. Mental Health Awareness Month also coincides with a time when our students prepare for the end of the year exams, making it a particularly valuable time for us to think about how we can continuously assist them during their time at university. The value of peer support and genuine care can never be overstressed; that is why I want to encourage our students to reach out to their support networks such as our Department of Student Counselling and Development, as we move towards the end of the year.
Mental health is an equally important matter for our staff. During this month, I want to encourage our staff to also take cognisance of their own well-being. There is a lot of wisdom in the old adage: Healthy body, healthy mind. Many of the initiatives of our Division of Organisational Development and Employee Wellness are focused on the value of physical activity and the negative impact that inactivity can have on one’s productivity and mental health. They also present regular lunch-hour sessions for our staff, where experts share information and practical tips for mental wellness. I want to encourage our staff to attend these sessions and to make use of the services the university has to offer in this regard. It is important to note that suffering from mental and anxiety disorders is not weaknesses and it is not always indicative of a deeper psychological issue; it is an illness and hence can be treated.
On 20 September 2019, a 21-member team was sent off on their run of 1 075 km to Stellenbosch to raise awareness for mental health. The run was organised by the Division of Organisational Development and Employee Wellness and the Faculty of Health Sciences. The team ran in relay format throughout the night and handed the baton of hope to Stellenbosch University on 25 September 2019. I admire and thank them not only for their commitment and stamina, but also for addressing this crucial matter in the public domain and for raising awareness in the many towns and communities along the way.
This is an excerpt from a message by Prof Francis Petersen.
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.