Latest News Archive
Please select Category, Year, and then Month to display items
05 April 2021
|
Story Dr Nitha Ramnath
|
Photo Supplied
Jamba Isaac Ulengo.
François van Schalkwyk and Keenan Carelse, UFS alumni leading the university’s United Kingdom Alumni Chapter, have put their voices together to produce and direct the podcast series. Intended to reconnect alumni with the university
and their university experience, the podcasts will be featured on the first Monday of every month, ending in November 2021. Our featured alumni share and reflect on their experiences at the UFS, how it has shaped their lives, and relate
why their ongoing association with the UFS is still relevant and important. The podcasts are authentic conversations – they provide an opportunity for the university to understand and learn about the experiences of its alumni and to celebrate
the diversity and touchpoints that unite them.
Our podcast guest
Born in the North West town of Vryburg, Ulengo first played provincial rugby at the U16 Grant Khomo Week in 2005. While attending Jim Fouché High School in Bloemfontein, Ulengo was chosen to represent the Free State at various youth levels. As
an up-and-coming player, Ulengo made his break via the FNB Varsity Cup Competition where he starred for the Shimlas, scoring 11 tries in 18 appearances over the three seasons between 2010 and 2012. A short stint with the Free State Vodacom Cup side
saw him make his debut for the Blitzboks (Glasgow 2012), followed by a tournament at the London Sevens in 2014. Ulengo has been a prominent member of the South African Sevens since making his debut for the team in the Scotland leg of the 2011-2012
IRB Sevens World Series. He played in the two final tournaments of that season and then signed a two-year contract with the South African Rugby Union to represent the team in the 2012-2013 and 2013-2014 series. While he only competed at four events
in his first full season, he was involved in seven of the tournaments in his second season.
Ulengo made his return to the sport by signing a contract to play Currie Cup rugby for the Pretoria-based Blue Bulls in 2014 and for their Super Rugby franchise, the Bulls, from the 2015 Super Rugby season.
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.