Latest News Archive

Please select Category, Year, and then Month to display items

UFS scholars recognised by Academy of Science

23 October 2020 | Story Andre Damons | Photo Supplied

Read More picture — Prof Johan H Meyer and Prof Hussen Solomon.

Two scholars from the University of the Free State (UFS) are among 31 of the country’s leading scholars and scientists who were inaugurated as new members of the Academy of Science of South Africa (ASSAf).

Prof Johan H Meyer from the Department of Mathematics and Applied Mathematics and Prof Hussein Solomon from the Department of Political Studies and Governance were inaugurated as members of the ASSAf during the annual award ceremony that was held virtually on 14 October 2020.

Looking forward to make a contribution

Prof Solomon says he is humbled to be included into the ASSAf family.

“Earlier this year, Prof Neil Roos asked if he could nominate me for ASSAf. This was done in March, after which I heard nothing until last week. What it means to me is an acknowledgment of my cumulative academic career spanning 31 years. I look forward to making a contribution via ASSAf towards the next generation of scholars and scholarship in SA,” says Prof Solomon.

Humbled and honoured

Prof Meyer says he was asked by the top management of the UFS to apply for membership, but his inclusion came out the blue.

“I feel humbled by this inclusion – to be welcomed in a community that is regarded scientifically significant. I never expected to be selected, but I am nevertheless satisfied with the contributions I could make, in particular to the mathematical community. I feel honoured, and trust that I will be able to live up to it for several years to come,” says Prof Meyer.

Serve as role models for younger academics

Prof Corli Witthuhn, Vice-Rector: Research and Internationalisation, said this honour was bestowed upon the two researchers whose work has been judged by their peers to have significant international impact.

“We are very proud of the two outstanding researchers who were selected as members of the Academy of Science of South Africa during 2020. They continue to serve as role models for our younger academics in natural science and in the humanities and social sciences who are striving to produce the highest quality research that is relevant to a local and international audience.”

As the official Academy of South Africa, ASSAf honours the country’s most outstanding scholars by electing them to membership of the Academy. ASSAf members are drawn from the full spectrum of disciplines. New members are elected each year by the full membership of the Academy is in recognition of scholarly achievement. Members are the core asset of the Academy and give of their time and expertise voluntarily in the service of society. The 31 new ASSAf members bring the total membership of ASSAf to 597.

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.

Back

Economic and Management Sciences

Education

Health Sciences

The Humanities

Law

Natural and Agricultural Sciences

Theology and Religion

Open Distance Learning

Business School

We use cookies to make interactions with our websites and services easy and meaningful. To better understand how they are used, read more about the UFS cookie policy. By continuing to use this site you are giving us your consent to do this.

Accept