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Dr Shezree Tiel graduates top of her class

13 December 2023 | Story André Damons | Photo Charl Devenish

As she achieved the goals she had set for herself, Dr Shezree Tiel, one of the latest graduates from the University of the Free State (UFS) Faculty of Health Sciences (FoHS), developed the courage to not only define her goals, but aim for even more. This is the reason she graduated not only summa cum laude, but as the top student in her year group.

Dr Tiel was one of 459 students who graduated on Friday (8 December 2023) during the FoHS’s December graduation ceremony. She graduated with a MBChB degree and is one of eight students to do so summa cum laude. During her five years of studies to become a medical doctor, she was the top student in each of her year groups.

“I feel very excited and still in disbelief, because it has been my dream since first year to graduate cum laude, but there were moments I felt I may have to accept that it may not be possible. So, I am very delighted that despite all the challenges I faced, my dream was realised,” she said.

According to her, she decided to study at UFS as it is the only university in South Africa that offered a five-year medical degree.

Building healthier and happier communities

Talking about how she achieved this, Dr Tiel, who will be doing her community service year in her home province of Mpumalanga, said what was consistent throughout her years of study, was the need to avoid a uniform approach to studying. Instead, she continued, she embraced different ways to learn.

Said Dr Tiel: “I embraced different ways to acquire knowledge and used these to identify a method of study that would be best suited for each module, chapter and sometimes each day. Everyday courage, resilience, patience, and perseverance played a vital role in accomplishing all my achievements. In spite of all of this, I will always attribute my achievements to my trust in Christ.”

Her desire to make the best possible use of every opportunity she gets to gain knowledge and the hope to use that knowledge to be useful to people and communities, motivated her on her journey to become a doctor. She decided to study medicine because she aspired to work with people in the pursuit of building healthier and happier communities. She believed that medicine would provide a great foundation and platform to accomplish this.

Though she is yet to decide in which field she would like to specialise one day, she believes it would be in internal medicine because it has always been one of her favourite rotations. “I do hope whichever one I go into will provide me with an opportunity to teach because that is one of the things I delight in.”

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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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