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24 July 2024
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The University of the Free State (UFS) is co-hosting the Global Social Innovation Indaba together with Social Innovation Exchange (SIX) on its Bloemfontein Campus from 30 September to 2 October 2024. This event brings together people from different sectors all over the world to discuss how to accelerate and support people-powered
change and create a better society for generations to come.
The UFS is excited to collaborate with SIX, as its vision and values overlap. During this three-day indaba, aspects such as – what it takes to build accountable, inclusive, and participatory institutions, specifically the future role of universities in South Africa – will be discussed. Themes to be explored include young people as drivers of change, post-industrial transitions and community resilience, the role of art, social change and bridging divides, and systemic approaches to dealing with unemployment.
Some of the speakers and participants in the programme include Carla Duprat from ICE (Brazil); Cheryl Jacob from ESquared Investments (South Africa); François Bonnici from the Schwab Foundation for Social Entrepreneurship (Switzerland); Sir Geoff Mulgan from the University College London (UCL) in the United Kingdom; and Dr Narissa Ramdhani from the Ifa Lethu Foundation (South Africa).
The UFS will also use the opportunity to showcase its campus and offerings to attendees, focusing on its transformation story and some of the interdisciplinary forward-thinking programmes. Guests will also be treated to true South African hospitality, laying the foundation for strong relationships and collaboration.
SIX believes in the transformative power of people working together. Exchanges based on mutual value and reciprocity are the missing link in tackling the world’s problems. As a friendly, expert entry point to global social innovation, their work connects organisations, sectors, communities, and nations to build capabilities and create opportunities for collaboration.
Mathematical methods used to detect and classify breast cancer masses
2016-08-10
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.