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10 November 2021 | Story Leonie Bolleurs | Photo Supplied
Prof Abdon Atangana was recently elected a fellow of The World Academy of Sciences (TWAS).

Prof Abdon Atangana, Professor of Applied Mathematics in the Institute for Groundwater Studies at the University of the Free State (UFS), was recently elected a fellow of The World Academy of Sciences (TWAS).

He also received the World Academy of Sciences Award for Mathematics (TWAS -Mohammad A. Hamdan, 2020) on 1 November 2021.

TWAS, described as the voice for science in the South, is working towards the advancement of science in developing countries and supports sustainable prosperity through research, education, policy, and diplomacy. 

Outstanding contribution to science

Prof Mohamed HA Hassan, President of TWAS, congratulated Prof Atangana on this prestigious achievement, “Your election as fellow is a clear recognition of your outstanding contribution to science and its promotion in the developing world. We will be honoured to have you among our members.”

Candidates elected as TWAS Fellows are scientists whose contributions to their respective fields of science meet internationally accepted standards of excellence, and they must have distinguished themselves in efforts to promote science in developing countries. 

Prof Atangana is known for his research to develop a new fractional operator, the Atangana-Baleanu operator, which is to model real-world problems. With this operator, he not only describes the rate at which something will change, but also account for disrupting factors that will help to produce better projections.

Among others, his models can advise people drilling for water by predicting how groundwater is flowing in a complex geological formation. Furthermore, his work can also be applied to predict the spread of infectious diseases among people in a settlement, forecasting the number of people who will be infected each day, the number of people who will recover, and the number of people who will die. 

These are only two examples of how his work can be applied to better the lives of people.

Promoting science in the developing world

Besides promoting science in the developing world, Prof Atangana’s work also contributes to the United Nations Sustainable Development Goals – the global goals as set in 2015 that call for ending poverty, protecting the planet, and ensuring that all people enjoy prosperity and peace.

Prof Atangana says the election as fellow is a clear recognition of his outstanding contribution to science and its promotion in the developing world. “My work over the past five years has made a great impact in all fields of science, technology, and engineering.”

To be elected as TWAS fellow in mathematics, made him the second South African researcher to be elected in the field of mathematics (the first person elected was Prof Reddy Batmanathan Dayanand, who was elected in 2003). This also placed him as the sixth African mathematician to be elected as a TWAS fellow.

Very recently, he also ranked number one in the world in mathematics, number 186 in the world in all the fields, and number one in Africa in all the fields, according to the Stanford list of 2% single-year table.

He was also named among the top 1% of scientists on the global Clarivate Web of Science list. Less than 6 200 or 0,1% of the world's researchers were included on this list in 2020, with no more than 10 of the scientists hailing from South Africa. 

Prof Atangana is also editor of more than 20 top-tier journals of applied mathematics and mathematics, and for some of these journals he was the first African to be selected as editor. 

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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