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2023 Ernst Mach Grant recipient from the UFS

16 August 2023 | Story Rorisang Ramorena | Photo Supplied

Michael Skosana, a student on the Bloemfontein Campus of the University of the Free State (UFS), has been selected as the recipient of the 2023 Ernst Mach Grant scholarship exchange programme at the University of Applied Sciences in Austria.

Skosana, currently pursuing his honours in Financial Economics and Investment Management at the UFS, aspires to pursue not only his master's qualification but also his Chartered Financial Analyst (CFA) levels and regulatory exams and ultimately pass his board exams. Skosana is set to leave on 30 August to start the semester on 1 September 2023.

About the grant

The Ernst Mach Grant is a program aimed at students from non-European universities who wish to spend a semester or two at an Austrian University of applied sciences. The Austrian Ministry of Science and Research offers the Ernst Mach Grant to students with non-European citizenship who plan to take up exchanges at an Austrian university.

According to its 2023 – 2028 internationalisation strategy, the UFS aims to integrate international and intercultural dimensions into the university's being, including the formal and informal curriculum. The Office for International Affairs (OIA) enables such comprehensive internationalisation, and specifically its International Scholarships portfolio, under the leadership of Mbali Moiketsi, contributes by liaising with funding bodies for mobility, sharing information about possible opportunities, and supporting students through the process.

The responsibility of the OIA is to ensure that students and staff are exposed to intercultural opportunities as part of their learning curriculum through information sharing. The OIA partners and works with international funding agencies to bring the information to the students and staff and support them through the process.

Skosana's motivation to study abroad is to challenge himself on the spectrum of finance, to learn more about the Austrian and South African economies, and, hopefully, to work in Europe and gain insight before returning home to change the financial landscape of South Africa. He added that “the acquired skills will empower and develop the South African financial economy and educate South Africans on financial literacy, investments, and any financial goals they seek knowledge about.”

Furthermore, Skosana encourages students to be more open to knowledge and international experiences by participating in such opportunities. He emphasizes that “students should always want to broaden their intercultural and global competencies beyond academics.”

For more information related to scholarships and opportunities, contact Mbali Moiketsi at the following email moiketsimv@ufs.ac.za

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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