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Faculty of Economic and Management Sciences Dean’s Medal winners

09 October 2020 | Story Dr Nitha Ramnath

EMS graduation — Jan Johannes van Niekerk and Pierré Ludwig Koekemoer

This year, two proud recipients of the Dean’s Medal were honoured during the 2020 UFS Virtual Graduation Ceremony. Jan Johannes van Niekerk received the award for the best results in respect of a Bachelor’s Degree in the Faculty of Economic and Management Sciences (Bachelor of Accounting), and Pierré Ludwig Koekemoer was awarded the medal for the student who achieved the best results in respect of a Bachelor Honours Degree in the Faculty of Economic and Management Sciences (Bachelor of Commerce Honours with specialisation in Marketing).

Jan Johannes van Niekerk

Prior to commencing his studies at the UFS, Van Niekerk attended Fichardt Park High School in Bloemfontein. Van Niekerk describes his time thus far as a student in the School of Accountancy as “nothing less than special”. He adds that “… the support from the lecturers is really great … every lecturer has always tried to help me to the best of their ability!”

His favourite subject is Financial Accounting, and his Financial Accounting lecturers inspired him to follow in their footsteps; accordingly, he became a Financial Accounting tutor in his second and third years of study. “As academic staff, we have come to know Johan as a pleasant and well-mannered, diligent, and hardworking student who pays attention to detail,” says Prof Frans Prinsloo, Director: School of Accountancy.

Johan is completing his BAcc Honours studies this year and will commence his training contract with Enslins Auditors in 2021 to qualify as a chartered accountant (SA).

Pierré Ludwig Koekemoer
“Pierré Koekemoer is one of the most decent young men I’ve met in years. Hardworking, diligent, and one of the most respectful and responsible people I know,” says Prof Brownhilder Neneh, Associate Professor in the Department of Business Management.

Pierre Koekemoer was identified as the Best Honours Student for 2019 in the School of Accountancy, as well as the student with the best Honours script. Koekemoer excelled during his Honours year, and successfully managed his responsibilities as student assistant/marker; he was also part of the City Lodge Marketing project that took place during the second semester.

The General Manager of the Fairview Hotel in Nairobi, Kenia, offered Koekemoer a short internship at the beginning of 2020, as he was impressed with his performance. Koekemoer could not accept the job, as he had obtained permanent employment and did not want to lose the position. “This also speaks of his integrity, as he had already committed to the company,” comments Prof Neneh.

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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