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15 March 2022 | Story Rulanzen Martin | Photo Supplied
Dr Khabele Motlosa and Prof Molefi Kete Asante
The keynote speakers are Dr Khabele Motlosa (right), Senior Lecturer in the Department of Political and Administrative Studies at NUL, and leading Pan-Africanist scholar Prof Molefi Kete Asante(left).

The Centre for Gender and Africa Studies (CGAS) at the University of the Free State (UFS), together with the National University of Lesotho (NUL) and the Academic Forum for Development of Lesotho, is hosting an online think tank on the transnational communities of the Lesotho-South Africa border from 19 to 21 March 2021.  The theme of the conference isLesotho and South Africa: a clarion call for a Pan-Africanist future. 

The keynote speakers are Dr Khabele Motlosa, Senior Lecturer in the Department of Political and Administrative Studies at NUL, and leading Pan-Africanist scholar Prof Molefi Kete Asante

Dr Munyaradzi Mushonga, Programme Director: Africa Studies Programme in CGAS, is the convenor of the conference and is also leading the UFS borderlands panel. The borderlands project is jointly funded by the Office of the Dean: Faculty of the Humanities at the UFS, and the National Institute for the Humanities and Social Sciences (NIHSS).

For more information and to register for the conference, click here

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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