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12 December 2024
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Dr Cias Tsotetsi, newly appointed Campus Vice-Principal: Academic and Research on the UFS Qwaqwa Campus.
The University of the Free State (UFS) is pleased to announce the appointment of Dr Cias Tsotetsi as the Campus Vice-Principal: Academic and Research on the UFS Qwaqwa Campus as from 1 January 2025.
He is currently Senior Lecturer and Assistant Dean in the Faculty of Education on the UFS Qwaqwa Campus. He holds the following qualifications: BEd(Hons), Postgraduate Diploma in Education, Magister Educationis with specialisation in Policy Studies and Governance in Education, and PhD with specialisation in Philosophy and Policy Studies in Education – all from the UFS.
Dr Tsotetsi operated in the school environment for about 24 years before joining this university in 2010. Since then, he has taught several modules in the Faculty of Education and published several co-authored research articles as well as conference papers on community engagement, teacher development, and participatory action research methodologies, among others. He is also well versed in supervising postgraduate students.
He has received awards from both the university’s Scholarship of Teaching and Learning and the Research committees for his research and academic scholastic performance. He is a member of various committees, such as the Faculty of Education Academic Advisory Board and the Committee for Title Registration and has been participating in partnerships and in NRF-funded projects with peers from universities such as the University of KwaZulu-Natal, the University of Zululand, the Durban University of Technology, and the University of Venda.
“Dr Tsotetsi has a clear understanding of the current systems and operations on the Qwaqwa Campus and is positioned to drive its development. His experience and initiatives involving staff and postgraduate students are exceptional and inspiring. We look forward to Dr Tsotetsi’s valuable contribution to the UFS Qwaqwa Campus and the institution in his new position,” says Prof Prince Ngobeni, Campus Principal of the Qwaqwa Campus.
“I feel honoured to serve the university – and the Qwaqwa Campus in particular – and look forward to working with the campus and its management to develop the research portfolio,” says Dr Tsotetsi.
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.