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21 July 2020 | Story Nitha Ramnath | Photo istock

Date: 28 July 2020
Time: 14:00 – 15:30

Gender inequalities domestic violence and gender-based violence (GBV) are global concerns, and have been exacerbated by the impact of Covid-19 as women take on more child and care work responsibilities.  Jobs lost in service sectors often affect women most, large numbers of frontline health workers and teachers are women, and lockdowns increase domestic violence. Thus President Cyril Ramaphosa recently said in a televised address that more than 21 women and children have been murdered in South Africa within just a few weeks in what he referred to as “another pandemic raging in our country.” He said this “violence being unleashed on women and children with a brutality that defies comprehension, is no less than a war being waged against the women and children of our country”.

As the World Economic Forum points out, regardless of where one looks, it is women who bear most of the responsibility for holding societies together, be it at home, in health care, at school, or in caring for the elderly. In many countries, women perform these tasks without pay. 

Now, the Covid-19 pandemic is compounding existing gender inequalities, and increasing risks of gender-based violence. Gender inequality, layered along with the effects of the pandemic, lockdowns and the economic downturn, could leave a deep and lasting impact on the lives and opportunities of women and girls.

Given, then, that the COVID-19 crisis affects women and girls in different ways from men and boys, measures to resolve it must take gender into account, and the protection and promotion of the rights of women and girls prioritized. 
To take up these issues of gender inequalities and gender-based violence, two renowned gender research experts will take part in our webinar. The webinar will be chaired by Professor Melanie Walker of the University of the Free State.  The presenters are: Professor Pumla Gqola, Professor of Women and Gender Studies at Nelson Mandela University and author of Rape: A South African Nightmare. Lisa Vetten has worked in the field of violence against women for over two decades as a counsellor, para-legal, trainer and researcher. She is currently an honorary research associate at the Wits Institute for Social and Economic Research (WiSER).

Join us from 14:00 to 15:30 on 28 July. 

RSVP to Sibongile Mlotya at MlotyaS@ufs.ac.za no later than 26 July, upon which you will receive a Business for Skype meeting invite.

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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