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31 January 2024
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Story EDZANI NEPHALELA
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Photo ANJA AUCAMP
Dr Martin Laubscher’s thesis, crowned with the Andrew Murray-Desmond Tutu Prize, is testament to the university’s unwavering commitment to scholarly excellence.
In a historic triumph that reverberates over four decades since its inception, the UFS has clinched the coveted
Andrew Murray Prize – now renamed the Andrew Murray-Desmond Tutu Prize – for the first time. Standing shoulder to shoulder with institutions such as the University of Pretoria (UP) and Stellenbosch University (SU), this achievement marks a significant milestone in the UFS’ journey.
At the heart of this accomplishment lies the profound contribution of
Dr Martin Laubscher, distinguished Senior Lecturer specialising in Practical and Missional Theology in the
Faculty of Theology and Religion. Dr Laubscher’s dedication and scholarly prowess culminated in the groundbreaking work titled
Publieke teologie as profetiese teologie? (Public theology as prophetic theology), a revised edition of his doctoral thesis, which was originally crafted at Stellenbosch University in 2020, with a focus on the eminent Karl Barth.
Dr Laubscher received the Andrew Murray Prize for Theological Books in Afrikaans for his research and insightful analysis. The journey started when he realised, under the guidance of his study leader,
Prof Dion Forster, that his script had the potential to be published in Afrikaans. Sun Media’s interest in publishing this work in Afrikaans, led to it being the first-ever published thesis in Afrikaans. Dr Laubscher recalls, “I was grateful and excited about Sun Media’s interest. The book emerged within a year, and during a celebratory launch Prof Forster suggested I submit it for the Andrew Murray Prize.”
Earlier this year, Dr Laubscher was excited to learn that he was being shortlisted for the prestigious award. Reflecting on the significant moment, he shares, “The elation I felt upon receiving the news was unparalleled. I was not only celebrating a personal triumph, but also etching my name as the first laureate from our faculty to secure this prestigious accolade.”
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.