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30 March 2021 | Story Cornelle Scheltema-Van Wyk
A cover image of the Perspectives in Education journal
Perspectives in Education (PiE) is one of the University of the Free State’s (UFS) accredited academic journals. Hosted on KovsieJournals with eight other accredited titles published by the UFS, PiE is a fully open-access journal, which means that all articles are freely available on the internet immediately after publication. A professional, peer-reviewed journal, PiE represents a variety of cross-disciplinary interests, both theoretical and practical, seeking to stimulate important dialogue and intellectual exchange on education and democratic transition with respect to schools, colleges, non-governmental organisations, universities, and universities of technology in South Africa and beyond.

Moving to the South Campus for Open Distance Learning 

The latest issue looked at the seismic disruptions brought about by COVID-19 in 2020, and the global challenges for education systems to promote and continue meaningful learning. Schools and colleges across the globe were closed, and teachers, students, schools, universities, and education planners had to create contingency plans. In the scholarly community, COVID-19 unsettled what we know, how we come to know, and how we should proceed from here onwards. It was the opportune moment for re-invigorated interrogation, rethinking discussion, and replanning education. An opportunity to rethink teaching and learning, the organisation of educational institutions, and the structure and workings of education systems, as well as to reflect once again on the objectives of education, and the interrelationship between education and society.

The issue features many national and international authors – from the UFS to authors from the United Kingdom, New Zealand, Zimbabwe, Israel, Brazil, and Haiti. Its diverse content comes from a relatively new editorial team. Prof Jan Nieuwenhuis’ first issue as editor-in chief was published in 2020. The move to the South Campus for Open Distance Learning was accompanied by the journal’s application to be included in the internationally renowned accreditation list, Directory of Open Access Journals (DOAJ). The DOAJ has strict inclusion criteria, and to be included on this list is a mark of a high-quality open-access academic journal. 

Just over a year after moving, PiE is now included in the DOAJ list and appears on four accredited lists (also DHET, IBSS, and Scopus). The journal has firmly cemented its place in the field of education and is broadening the reach of research for the University of the Free State

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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