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05 November 2020 | Story Thabo Kessah
Prof Moffett’s latest offering collates hundreds of mountain research material into one accessible reference book.

Prof Rodney Moffett recently published a new book focusing on various scientific articles published between 1808 and 2019. The book, A Scientific Bibliography of the Drakensberg, Maloti and Adjacent Lowlands, has 534 pages and covers material appearing in accredited journals, plus unpublished but traceable reports, documents, presentations, and dissertations.

“The scientific articles range from palaeobotany with 17 entries, to rock art with 502 entries, as well as 252 theses and dissertations,” said Prof Moffett.

He said it took 18 months to compile the book, typing the manuscript himself – mostly at night.

In the foreword, Dr Ralph Clark, Director: Afromontane Research Unit (ARU), says: “This bibliography is a labour of love, and will inspire a new generation to take up the baton for excellent research in this fantastic mountain system. We are proud to publish this under the ARU banner as a contribution to growing and consolidating mountain-passionate relationships in Southern Africa, and to encourage our journey towards developing a holistic understanding and sustainable use of these iconic mountain landscapes.” 

Other books

Prof Moffett is an honorary research fellow in the Department of Plant Sciences at the University of the Free State, and an associate of the Afromontane Research Unit on the UFS Qwaqwa Campus. He was previously Professor of Botany on the Qwaqwa Campus when it was part of the University of the North, retiring in 2000. Since then, he has remained active, publishing scholarly works on ethnobotany and other natural history subjects.

His four recent books, also published by Sun Press, are: Sesotho Plant and Animal Names and Plants used by the Basotho (2010), A Biographical Dictionary of Contributors to the Natural History of the Free State and Lesotho (2014), Basotho Medicinal Plants – Meriana ya Dimela tsa Basotho (2016), and A Field Guide to the Clarens Village Conservancy (2018). A second revised edition of Meriana ya Dimela tsa Basotho – 

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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