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16 July 2020 | Story Valentino Ndaba
Add these emergency safety contacts to your speed dial.

Staying safe during the coronavirus pandemic extends to ensuring that students at the University of the Free State (UFS) are safe from crime. Crime in South Africa remains an unfortunate reality which continues to affect students, staff and the institution in general. 

“Crime requires constant vigilance from the community and this can only be achieved through initiatives that are aimed at informing the community on what to do and what not to do. To this end the BSafe Safety First flyer is geared at informing specifically the student community on safety measures that must be taken,” said Cobus van Jaarsveld, Assistant Director: Threat Detection, Investigations and Liaison at Protection Services.

The Safety First flyer is a guide for students to be crime-conscious whether at their accommodation, on the street, or in their vehicles. It also offers tips on how to act responsibly as far as alcohol and drugs are concerned.

Engaging students on their safety 

UFS Protection Services recently engaged with off-campus residence students in Bloemfontein in order to provide tips on how to stay safe in their neighbourhoods. During the engagement, the new Safety First pamphlets were distributed, and students were encouraged to join the Student Crime-Stop Brandwag WhatsApp group.

As from 15 June 2020, Nissi Armed Response was deployed from 18:00 to 06:00. This initiative has already led to them responding to several suspicious persons and vehicles, as well as some minor incidents and disturbances. Two arrests were made on different occasions as a result of the deployment. In the first incident, a suspect was arrested on 27 June 2020 after a burglary in Brandwag, and the second relates to a suspect who was arrested on 10 July 2020 after threatening students at Universitas.

These successes were the result of student and community participation in providing information, coupled with excellent response from private security companies, including Nissi Armed Response, VR Security, and BloemSec.

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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