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21 May 2019 | Story Thabo Kessah | Photo Ian van Straaten
Dr Thandi Gumede
Dr Thandi Gumede graduated with a PhD in Polymer Science. She is from Intabazwe, Harrismith.

The Qwaqwa Campus of the University of the Free State was a hive of activity on 17 and 18 May 2019, when over 800 degrees, diplomas, and certificates were conferred on deserving achievers. These included six PhDs and 14 master’s degrees across the four faculties.

Congratulating the graduates on both days, was Africa’s youngest PhD and Industrial Psychology lecturer, Dr Musawenkosi Saurombe, and Prof Francis Petersen, Rector and Vice-Chancellor.

Be like heat

Dr Saurombe started her address by relating her school journey that saw her starting Grade 1 at age 5, thus later matriculating at the age of 15, having skipped Grades 3 and 10. She went on to emphasise the importance of building an honourable character.

“As a graduate, you will soon realise that your degree is useless if you do not have character,” she said to an attentive audience that continued to marvel at her remarkable school history. She encouraged graduates to be like heat that cannot be seen but can only be felt. “Noise can often be seen and heard, but it cannot be felt. However, while heat cannot always be seen, it is always felt. Be like heat and may your presence always be felt,” she said.

Do not focus on yourself

Prof Francis Petersen also encouraged graduates to look beyond their degrees by developing a set of critical values.
 
“For us as the university, this ceremony is not just about your degrees. It is about the values that you must live by,” he said. “As a graduate of the UFS, do not just believe what you are told. Ask questions and engage critically. Secondly, do not just focus on yourself. Remember that you are part of a community and it is your responsibility to make our world a better place for others. You need to be socially responsive to the needs of your community. Thirdly, remember that integrity plays a very important role. This will determine how others value you,” he said.

The two ceremonies also saw three current SRC members graduating. They are Lebohang Miya (BEd FET – Accounting and Business Studies), Duduzile Mhlongo (BA – Geography and isiZulu), and Mhlongo Sinemfundo (BA – Geography and isiZulu).

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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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