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19 November 2019 | Story Annali Fichardt

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The South African Nursing Council (SANC), the Council of Higher Education (CHE), and the South African Qualifications Authority (SAQA) have approved the curriculum for the Bachelor of Nursing at the University of the Free State (UFS).
 
Prospective students are encouraged to apply as soon as possible, but no later than 4 December 2019, to be considered for the first selection committee scheduled for 9 December 2019. Selection will be based on academic performance. 
 
According to the SANC, only 75 students can be registered for the Bachelor of Nursing at the UFS State in 2020.

The minimum requirements to apply for a Bachelor of Nursing are:
 
1.           Admission Point (AP)        30
2.           Language of instruction    50%
3.           ** Mathematics                 40% or Mathematical Literacy 70%
4.           ** Life Sciences                60% or Physical Sciences  50%
 
**       Either Mathematics or Mathematical Literacy is required, as well as either Life Sciences or Physical Sciences.
 

•         Please ensure that your application (with all the supporting documents, including a medical certificate) is complete. 
•         Incomplete applications will not be considered for selection.

 
Any enquiries about the application process can be directed to Klopper1@ufs.ac.za


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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