Latest News Archive

Please select Category, Year, and then Month to display items
Categories
UFS News Media Release Research
Years
2017 2018 2019 2020 2021 2022 2023 2024
Months
January February March April May June July August September October November December
Previous Archive
03 April 2019 | Story Xolisa Mnukwa | Photo Vhugala Nthakheni
Uhuru Qwaqwa Arrival
The #UFSWalkToUhuru team arrives at the UFS Qwaqwa Campus on Friday 22 March.

The University of the Free State (UFS) Division of Student Affairs, in collaboration with the UFS Office for International Affairs, have joined hands to drive a fundraising and student-accessibility initiative dubbed, ‘The Walk to Uhuru’ (#UFSWalktoUhuru), which is aimed at raising funds and advocating for the educational rights of the less privileged. 

The project aims to raise funds in excess of R2 million from the public and stakeholders affiliated with the UFS (Kovsie staff and students). The project derives from the 2018/2019 UFS Institutional Student Representative Council (ISRC) mandate ‘Students Must Graduate’. The ISRC mandate aims to source funding opportunities for UFS students to register, and to complete their studies across all three campuses in 2020 and beyond.

The first leg of the project, a 350 km walk from the Bloemfontein to the Qwaqwa Campus, has already taken place and concluded on Friday, 22 March 2019 as planned. The #UFSWalkToUhuru team successfully completed the first leg of their journey to academic freedom for financially disadvantaged students at the UFS. The Uhuru team is now focusing its attention on the second leg and is determined to take on Mount Kilimanjaro (Uhuru) from 20 June to 20 July 2019.

The team sat down for a debriefing session to unpack the overall experience and result of the first half of the initiative, and they all agreed that the walk to Qwaqwa was an enlightening experience. It was a walk that comprised learning opportunities, team building, and goal crushing.

According to Rethabile Motseki, member of the #UFSWalkToUhuru team, the walk to Qwaqwa made a significant impact on the project, as the university community is now aware of the significant goals that the team is trying to accomplish. The team has also resumed their fitness-training programme to ensure that they are ready to take on the Uhuru climb in June.

A media briefing will take place shortly (date to be confirmed) to detail the ongoing fundraising initiatives rolled out by the #UFSWalkToUhuru team.  We implore you, and the nation as a whole, to help establish a better future for disadvantaged UFS students by donating to the initiative.

Students, staff, and the public can support the cause and make contributions/donations to the initiative by visiting the UFS Walk to Uhuru #givengain account page.

For more information, contact UFS SRC President, Sonwabile Dwaba, on DwabaSJ@ufs.ac.za  or Rethabile Motseki on MotsekiR@ufs.ac.za  

Dr Martin Mandew, Qwaqwa Campus Principal
Dr Martin Mandew, Qwaqwa Campus Principal
#UFSWalktoUhuru arrives the Qwaqwa Campus
#UFSWalktoUhuru arrives the Qwaqwa Campus
Final day of #UFSWalktoUhuru 4
Final day of #UFSWalktoUhuru 4
Final day of #UFSWalktoUhuru 3
Final day of #UFSWalktoUhuru 3
Final day of #UFSWalktoUhuru 2
Final day of #UFSWalktoUhuru 2
Final day of #UFSWalktoUhuru
Final day of #UFSWalktoUhuru
#WalkToUhuru 10
#WalkToUhuru 10
#WalkToUhuru 9
#WalkToUhuru 9
#WalkToUhuru 8
#WalkToUhuru 8
#WalkToUhuru 7
#WalkToUhuru 7
#WalkToUhuru 6
#WalkToUhuru 6
#WalkToUhuru 5
#WalkToUhuru 5
#WalkToUhuru 4
#WalkToUhuru 4
#WalkToUhuru 3
#WalkToUhuru 3
#WalkToUhuru 2
#WalkToUhuru 2
#WalkToUhuru 1
#WalkToUhuru 1

News Archive

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.

We use cookies to make interactions with our websites and services easy and meaningful. To better understand how they are used, read more about the UFS cookie policy. By continuing to use this site you are giving us your consent to do this.

Accept