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26 July 2022
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Story Bulelwa Moikwatlhai
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Photo Supplied
Experiencing the UFS in person for the first time are from the left: Sandor Potjer (VU Amsterdam), Bulelwa Moikwatlhai (UFS OIA), Ricarda Kochems (Bremen University, Germany), Froukje Pronk (VU Amsterdam) and Matome Mokoena (UFS OIA)
As the UFS COVID-19 Regulations and Required Vaccination Policy has been lifted with immediate effect – allowing 100% capacity of both students and staff members and a fully operational campus – the
Office for International Affairs welcomes its first physical exchange cohort after two years. The cohort of students hail from the various international partners of the UFS, namely the
University of Bremen in Germany, the Vrije Universiteit Amsterdam, and Sciences PO Bordeaux in France. The students will be hosted in the UFS faculties of the Humanities, Economic and Management Sciences, and Natural and Agricultural Sciences, respectively.
These students have been paired with
Umoja Buddy Programme ambassadors to help ensure their smooth transition and integration into student life at the UFS. Furthermore, the students received an invitation from the President of the
International Student Association (ISA), Courtney Madziwa, to join their association, thus exposing them to students from other countries to learn about the various cultures.
On 18 July, the Office for International Affairs (OIA) arranged a hybrid orientation programme for the exchange students, including those students who have not yet arrived on the Bloemfontein Campus. The students took part in an icebreaker activity, where they had the opportunity to learn from and teach other participants about their home countries. Dr Cornelius Hagenmeier, Director of the OIA, welcomed the exchange students to the Bloemfontein Campus, and expressed excitement to have physical exchanges again. Furthermore, the guest presenters ranged from student leadership, staff members, and service providers.
The presentations were practical, demonstrating, among others, how to create a password on the institutional website – presented by Mr Molemo Mohapi from UFS ICT. The presentation on how to fully utilise Blackboard was facilitated by Ms Vuthihi Mudau from the UFS CTL division. We take the safety of all our students seriously, so Ms Elise Oberholzer from the UFS Protection Services has given the students some tips on how to safeguard themselves.
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.