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27 December 2021
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Story Jóhann Thormählen
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Photo Supplied
The Kovsie Annerie Dercksen is one of South Africa’s most promising youngsters and climbing the cricketing ladder.
She enjoyed every second of playing with some of her heroes and believes the exposure to international cricket will help her become a better player.
Annerie Dercksen is one of South Africa’s most promising youngsters and climbing the cricketing ladder.
Star from Beaufort West
This second-year Education student from the University of the Free State (UFS), who dreams of playing for the Momentum Proteas, represented the South African Emerging Women’s team three times in 2021.
The star from Beaufort West toured with the side to Bangladesh and also played against Zimbabwe and Thailand in One Day and T20 matches.
According to Dercksen, it is an incredible honour and privilege to be a part of a side.
She soaked up the experience and says everyone was willing to share their knowledge.
“I would have to say, sharing the field with some of my heroes and getting to work with some of the best coaches in the country are some of the highlights.”
She says each tour brought its own challenges and this helped her grow in the way she views and approaches the game.
“In Bangladesh we played against a well-established team in foreign conditions while facing a lot of spinners in spin friendly conditions. Personally, it was quite a challenge and I had to come back and work on some options, especially against spin.”
“Each tour brought its own challenges and this helped me grow in the way I view and approach the game.” - Annerie Dercksen
Coming through the ranks
The all-rounder has come through the ranks. She represented South-Western Districts at school level, played for the South African U19 side and is currently representing the Free State.
But Dercksen didn’t always dream cricket, especially not when playing ‘backyard’ cricket with her brother on the farm.
She didn’t even play for a team at school. “Until a boy from our primary school’s team got sick before a game. A teacher came to class and asked, ‘who can play cricket’, and I put up my hand.”
Mathematical methods used to detect and classify breast cancer masses
2016-08-10
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.