Latest News Archive
Please select Category, Year, and then Month to display items
23 November 2022
|
Story André Damons
![]()
Prof Motlalepula Matsabisa, Professor and Director of Pharmacology, will play host to the various stakeholders to network and share knowledge on current developments in indigenous knowledge research and product development, biodiversity, innovation, and commercialisation of the IK-based research products. The Indigenous Knowledge System (IKS) for Health unit in the Department of Pharmacology within the UFS Faculty of Health Sciences was last year awarded an annual Technology Innovation Agency Platform (TIA) grant of R17 million for the next five years.
The research and teaching programme in the School of Clinical Medicine has since been rebranded and is now known as the African Medicines Innovation and Technology Development Platform (AMITD), which will strive to respond to community health needs and address industry research needs and challenges.
The indaba will showcase progress made by TIA and other entities in enriching the development and commercialisation of IK-based innovations. It will take place from 24 to 25 November 2022 in the Equitas Senate Hall at the UFS.
Prof Matsabisa is the chairperson of the World Health Organisation’s (WHO) Regional Expert Advisory Committee on Traditional Medicines for COVID-19. He is also a visiting professor at the Beijing University of Chinese Medicine (BUCM) in Beijing, China, and the Deputy President of the South African Society for Basic and Clinical Pharmacology.
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.