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26 January 2019
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The executive management of the University of the Free State (UFS) has noted with concern the disconcerting effects of the current political and economic crisis and instability in Zimbabwe – specifically with regard to the effect it has on its students from Zimbabwe.
“As part of a coordinated support effort driven by the UFS Office for International Affairs we have invited Zimbabwean students to communicate their individual challenges regarding finance, travel, and special examinations to us.
We have received various reports about problems with delayed visas and have appealed to the Department of Home Affairs to consider concessions for our affected Zimbabwean students,” says Mr Cornelius Hagenmeier, Director of the university’s Office for International Affairs.
Arrangements are being made on a case-by-case basis for students who were unable to register before the closing date. Students who have reported travel challenges are also being contacted individually to consider possible support.
“As an institution committed to the furtherance of social justice – not only on our campuses, but also in the wider Southern African region – the UFS wants to encourage our affected students not to abandon their all-important education plans in the light of the turmoil and obstacles they are currently facing. As a university community, our heartfelt sympathy goes to our Zimbabwean students and their families during these trying times,” says Prof Francis Petersen, UFS Rector and Vice-Chancellor.
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Lacea Loader (Director: Communication and Marketing)
Telephone: +27 51 401 2584 | +27 83 645 2454
Email: news@ufs.ac.za | loaderl@ufs.ac.za
Fax: +27 51 444 6393
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.