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04 April 2024
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Story Lunga Luthuli
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Photo SUPPLIED
Dr Juliet Kamwendo champions gender-inclusive climate action in Africa. Her expertise at the recently held AFR100 workshop highlighted vital steps towards sustainable and equitable development.
Dr Juliet Kamwendo, Lecturer and Programme Director for Gender Studies in the Centre for Gender and Africa Studies at the University of the Free State, is spearheading efforts to integrate gender considerations into Africa's climate restoration agenda. Reflecting on her involvement, Dr Kamwendo stated, "This is particularly crucial, as women make up almost 50% of the population in Africa, and the depletion and degradation of land affect them disproportionately."
She recently served as a gender expert at the AUDA-NEPAD AFR100 workshop in Ouagadougou, Burkina Faso, from 25 to 29 March 2024. This initiative aims to restore forests and degraded land across Africa by 2030, with a focus on gender equality.
The workshop emphasised the integration of gender perspectives into the AFR100 project, acknowledging the disproportionate impact of land degradation on women. Dr Kamwendo's expertise highlighted the need to empower women in climate change interventions, addressing existing gender inequalities exacerbated by environmental degradation.
“Women – who are primarily responsible for household food security and water provision – bear the brunt of environmental degradation, leading to increased workloads, reduced income opportunities, and heightened vulnerability to climate-related disasters. Furthermore, the loss of forest cover and biodiversity further exacerbates the challenges faced by women, particularly in rural areas where they depend heavily on natural resources for their livelihoods,” added Dr Kamwendo.
Her participation highlights academia's crucial role in fostering inclusive and sustainable development, emphasising interdisciplinary collaboration to tackle complex environmental challenges. Through initiatives such as AFR100, stakeholders are working towards a more resilient and gender-responsive future for Africa.
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.