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02 September 2020 | Story Lacea Loader | Photo Charl Devenish
Deputy Minister visit
From the left are: Deputy Minister of Higher Education, Science and Technology, Buti Manamela; Prof Prakash Naidoo, Vice-Rector: Operations at the UFS; and Dr Ramneek Ahluwalia, Chief Executive Officer of Higher Health.
“The work that the University of the Free State (UFS) is doing to ensure that students get the necessary support is quite impressive. The university is saving the academic year to save lives.” These were the words of the Deputy Minister of Higher Education, Science and Technology, Buti Manamela, during a visit to the university’s Bloemfontein Campus on 31 August 2020.

The visit was part of the Deputy Minister’s visit to higher education institutions in Bloemfontein to assess the academic state of readiness and to monitor the safety protocols for the phased re-opening of campuses during Level 2 of the national lockdown.

The delegation, which also consisted of representatives from Higher Health led by the Chief Executive Officer Dr Ramneek Ahluwalia, attended a briefing session in the Council Chambers before visiting various venues on campus. In his opening and welcoming remarks, Prof Prakash Naidoo, Vice-Rector: Operations, said that the safety, health, and well-being of staff and students remain the university’s priority. “Extensive planning has gone into making sure that the university complies with the national COVID-19 protocols and regulations and that our campuses are safe and ready for the return of students. Sufficient hygiene measures are in place, as well as adaptions to ensure physical distancing. The wearing of masks, physical distancing, and hand sanitising remain compulsory on all the campuses,” said Prof Naidoo.

“A Special Executive Group (SEG) was already established by the Rector and Vice-Chancellor, Prof Francis Petersen, at the beginning of March 2020. The SEG meets weekly to discuss and decide on the university’s response to COVID-19 as this pandemic develops over time. Consisting of eight task teams, the SEG is the decision-making entity that responds rapidly and in a coordinated manner to combat the threats to business continuity. One of the task teams is specifically looking at the wellness of our students and staff to make sure that this important aspect is taken care of,” said Prof Naidoo.

During a presentation of the university’s Multimodal Teaching and Learning Plan for the completion of the 2020 academic year, Prof Francois Strydom, Senior Director: Centre for Teaching and Learning, said that the university has an evidence-based approach towards remote multimodal teaching, learning, and assessment. “For instance, our vulnerable students were identified early in the lockdown, and 16 strategies were put in place to ensure that no student is left behind. 99,95% of our students were active on Blackboard. We are developing plans for the 0,05% of students who were not able to participate in learning, so that they can continue their learning journey with the UFS,” said Prof Strydom.

In his closing remarks, Deputy Minister Manamela commended the university management on the initiatives to save the academic year. He also indicated his appreciation for the informative session and encouraged the university to keep on motivating students and staff to be attentive to their behaviour and to remain careful about their health and well-being.

The programme was concluded with a visit to a number of venues on campus, including the examination venues, the Health and Wellness Clinic, the Pathogen Research Laboratory of the Division of Virology and a student housing unit.

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.

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