Latest News Archive
Please select Category, Year, and then Month to display items
09 December 2020
|
Story Carli Kleynhans
|
Photo Supplied
Carli Kleynhans.
With the most gruelling year recorded in our entire lives, gradually coming to an end we remain hopeful and thankful that we have made it through. From the unexpected shock of going into lockdown, to the worry of having to use a blended approach to succeed in your academics and now finally settling into a new normal, we at the advising office bestow upon you the title of Kovsie champion…because that's exactly what you are!
One of our many champions, Carli Kleynhans, a 3rd (final) year student enrolled for BA Psychology and English shares how she survived…no, actually how she has thrived in 2020.
• What was your biggest concern about your academics when you found out the country was going into lockdown?
My biggest concern about my academics as a final year student was whether the online learning and tests would provide the same in depth learning experiences that are necessary to build upon for future studies.
• What are some of the challenges you've experienced along the way?
Staying focused and trying not to procrastinate was a big challenge I had to conquer, especially trying to not be distracted by my family and my phone. How I survived and was able to thrive in 2020!
• What are some of the strategies you've used to ensure your academics don’t suffer?
Time management was one of the most important strategies that I applied. For most of my classes, I was able to focus each week on a different module, by working and studying in advance I was able to keep up with my workload and still have the weekends to focus on myself, therefore creating designated time to work, study and also time to relax and read.
• What support have you received from the institution that's helped you thus far?
Most of my lecturers have provided needed support regarding our academics. The institution helped provide clarity with everything that was going on.
• What do you think the UFS could have done differently to support student success?
I think the UFS could have provided more resources for the final year students, especially considering we have to apply for further studies; online it was difficult to discern exactly what was necessary for the applications, whereas in class I feel more information would have been provided.
• What has kept you motivated?
Knowing it is my final year has helped to motivate me, as I have to use these grades to apply for further studies. I recently received recognition from Golden Key and this helped to further inspire me to work even harder at my academics.
• What advice do you have for your fellow Kovsies who are finding it difficult to keep going?
Remember to make time for yourself, to look after yourself and your mental health, especially in these difficult times. Work in advance and keep to your personal academic calendar.
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.