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05 April 2022 | Story Lacea Loader
Qwaqwa Campus

The preliminary finding of the urgent investigation into the fire on the Qwaqwa Campus of the University of the Free State (UFS) on the evening of Monday 4 April 2022, indicates that the two buildings were intentionally set alight. This was established by the South African Police Service (SAPS) and the university’s Protection Services this morning.

Since the outbreak of the fire, one person – who is a registered student – has been arrested by SAPS, and a process is underway to identify more suspects. The UFS will institute the necessary disciplinary action against suspects who are registered students. Similarly, criminal charges will also be instituted.

The buildings, which housed the clinic and a computer laboratory, were almost completely destroyed, with damage to both buildings estimated at R35 million.

The university management condemns the destructive behaviour of the students and condemns criminal behaviour such as this in the strongest terms. “The Qwaqwa Campus, as well as the entire university community, are shocked by this devastating and irresponsible act – especially after the campus experienced violent protest action this year, which significantly affected the academic programme,” said Prof Francis Petersen, Rector and Vice-Chancellor of the UFS.

The academic programme on the Qwaqwa Campus continues, mostly online for this week, and students will be informed by their faculties about the revised schedule, as well as arrangements regarding tests and assessments scheduled for this week on the campus.

The campus remains open; the university's Protection Services is on high alert and is monitoring the situation on campus closely.

It is alleged that students were unhappy about the payment of allowances they are due to receive from the National Student Financial Aid Scheme (NSFAS) in April 2022. To alleviate this, the UFS has so far this year offered students allowances for food and books amounting to more than R71 million, while they are waiting for their NSFAS subsidies to be released. 


Released by:
Lacea Loader (Director: Communication and Marketing)
Telephone: +27 51 401 2584 | +27 83 645 2454
Email: news@ufs.ac.za | loaderl@ufs.ac.za


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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