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25 August 2020 | Story Andre Damons | Photo Pierce van Heerden
Prof Felicity Burt is a passionate virologist with more than 25 years of research on medically significant viruses that cycle in nature and are transmitted to humans via mosquitoes, ticks, or animals.

Prof Felicity Burt, an expert in arbovirology in the Division of Virology, has been leading the University of the Free State (UFS) COVID-19 Task Team over the past five months. Prof Burt is a passionate virologist with more than 25 years of research on medically significant viruses that cycle in nature and are transmitted to humans via mosquitoes, ticks, or animals.

As the UFS is celebrating its champion women this Women’s Month, Prof Burt gives us some insight into who she is. 

Please tell us about yourself

I am an arbovirologist from the Division of Virology in the Faculty of Health Sciences, and the National Health Laboratory Service. Who am I? I am a mum, a wife, a daughter, a sister, a sister-in-law, a friend, a scientist, a colleague, a professor.  I am passionate about my work and have spent more than 25 years researching medically significant viruses that cycle in nature and are transmitted to humans via mosquitoes, ticks, or animals. 
My research group investigates the various mechanisms that viruses use to cause disease, and I am particularly interested in how our bodies respond to infection that can help us develop vaccines or therapies. Raising awareness of these viruses, profiling disease associated with different viruses, and developing tools for surveillance programmes all contribute towards understanding pathogens and the public-health implications. I am so grateful for the opportunities my career has provided me, which includes travelling all over the world for conferences and meetings and participating in outbreak responses in Africa.   
   
Is there a woman who inspires you and who you would like to celebrate this Women’s Month, and why?

I am inspired by all women who set goals and work to achieve them. The goals may vary, but they are important and challenging to each individual.  Hence, I would like us to acknowledge and celebrate all women who achieve their goals through hard work, dedication, and of course, plenty of passion. 

What are some of the challenges you’ve faced in your life that have made you a better woman?

I have always been quite a shy person and still find it challenging to stand up in front of an audience. I was born in Zimbabwe and when I finished school, I moved to South Africa to study at the University of the Witwatersrand. Moving on my own to Johannesburg at the age of 18 was definitely a challenge for a quiet, reserved girl from Harare. Compared to home, Johannesburg was a mammoth city; however, I absolutely loved university life, met people who became lifelong friends, and pursued a career in science. I try to learn from my many mistakes and treat others how I would like to be treated, especially with kindness. 

What advice would you give to the 15-year-old you?

Dream on girl, and it doesn’t matter if they don’t all come true; life isn’t going to turn out as expected, but as long as you enjoy the journey. You don’t have to be the best, but you have to do your best – with passion of course. 

What would you say makes you a champion woman [of the UFS]?

To be honest, I wouldn’t call myself a champion, but I am quite proud of what I have established at the UFS. With hard work and passion, contributions from colleagues, support from management, and never forgetting a whole bunch of wonderfully enthusiastic students, we have built an active postgraduate research group, graduated multiple students, published scientific articles in international journals, presented our research at conferences, contributed to community engagement, had fun, and still have plenty more to achieve!  

 

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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