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22 April 2021 | Story NONSINDISO QWABE | Photo Thabo Kessah
Faith Mudzingiri.

Sharing her father’s love for the field of commerce, Faith Mudzingiri, daughter of Dr Calvin Mudzingiri, Assistant Dean of the Faculty of Economic and Management Sciences, is one of the more than 1 500 students who received their qualifications during the University of the Free State Qwaqwa Campus virtual graduation ceremony. Faith obtained her BCom General Management degree during the virtual ceremony on 21 April.

In 2020, Mudzingiri topped the academic charts as the best student across all faculties on the campus.

Following in the footsteps of her father

An accounting enthusiast from an early age, Faith said her father has been her biggest motivation. Having a parent in such a critical position can come with immense pressure to perform, but she said “watching him inspired me a lot. For me to be here, is because I’ve learned from him that hard work pays off”.

Mudzingiri said while she was grateful for the accomplishment of being the Dux student for 2020, her academics did not get off to a good start in 2017 when she began her first year.

“As an international student coming from Zimbabwe, I struggled a lot in my first year. I had difficulty finding my feet in the new environment. Things got better in my second year, but in my third year I reminded myself why I was here and why I started this degree. I knew I wanted to graduate in record time, and so had to put in the work.”

Still set on achieving her accounting dream, Mudzingiri is now pursuing a BCom Accounting degree on the Bloemfontein Campus. “I would love to become a tax accountant and start my own accounting firm one day.”

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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