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11 July 2022 | Story Lunga Luthuli | Photo Supplied
From the left: Dr. Annelie De Man (Coordinator - advocacy division - Free State Centre for Human Rights), Deputy Minister John Jefferey, Department of Justice and Constitutional Development, Martie Bloem ( Private Law Lecturer, Faculty of Law), Tshepang Mahlatsi (Student Assistant - Advocacy division) and Prof Danie Brand (The Director of the Free State Centre for Human Rights).

According to the international market and consumer data company Statista’s June 2022 data, more than 4,6 billion people worldwide are using social media; this is an increase of 1 billion people compared to the total users in 2020. 

Delivering his lecture on ‘Social Media, Freedom of Expression, and the Law’ on the University of the Free State Bloemfontein Campus on 30 May 2022, John Jeffery, Deputy Minister of Justice and Constitutional Development, said, “The power of social media lies in the sheer magnitude of the number of people using it.”

He said: “Section 16 of the South African Constitution provides that everyone has the right to freedom of expression, which includes freedom of the press and other media; freedom to receive or impart information or ideas; freedom of artistic creativity; and academic freedom and freedom of scientific research.”

He advised perpetrators of malicious social media posts about the consequences and the harm to persons who are victims.

Depending on the circumstances, a person who suffers harm because of being the subject of someone else’s social media posts, can be protected under the Protection from Harassment Act. According to the Act, this is due to mental, psychological, physical, or economic harm.

Speaking at the Odeion School of Music, Deputy Minister Jeffery said, “Social media brings with it the importance of responsible use. As a social media user, you are entirely responsible for whatever appears on your social media accounts.’

He said: “Whatever you do in life – your conduct and your words – can be put onto various platforms and they will be there for a very long time. Do better, be better – and use social media to inspire people, to have an impact on the world, and to make it a better place.”

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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