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20 December 2019 | Story Charlene Stanley | Photo Anja Aucamp
Sprouting Hope
Shadei Lepholletse, BSc Genetics and Physiology; Masabata Sebusi, BCom Accounting; and Tumelo Zondi, BCom Entrepreneurial Management; three of the directors of Sprout Africa, an agriculture and agri-processing company - the perceived potential of which has earned them each a place on the list of News24’s 100 Young Mandelas of the Future.

Enactus, 100 Young Mandelas of the Future, Sprout Africa, Masabata Sebusi, Shadei Lepholletse, Tumelo Zondi, and Farai Mzungu

Kovsie students’ innovative agri-processing venture is paying off. Two years ago, a seed of resolve was planted in four young UFS women. They entered the Enactus National Competition for entrepreneurship projects –and came stone last.

But instead of giving up, they re-grouped, re-evaluated their priorities, and came up with an innovative agri-processing community-upliftment concept that has earned each of them a place on News24’s list of 100 Young Mandelas of the Future.

“We asked ourselves what the big businesses out there were looking for when it came to community development. At that stage, we focused on arts and crafts and recycling. But we realised the need was for projects providing solutions around food insecurity, water management, and sustainable development,” explains Masabata Sebusi, final-year BCom Accounting student.

Masabata and her three partners, Shadei Lepholletse, Tumelo Zondi, and Farai Mzungu, are all studying in different fields. They pooled their diverse insights, knowledge, and perspectives. And Sprout Africa was born.

The company’s aim is to give people in rural communities training in modern farming techniques, equipping them with basic business skills and helping them to find an outlet for their produce. As part of the process, the women approached potential business partners – from local supermarkets to big commercial companies – to negotiate on behalf of the farmers.

This time, they seem to have struck the right nerve. Having won various grants while the concept as still an Enactus project, they have since registered Sprout Africa as a company. Various stakeholders have already shown interest to partner with them.

Their main advice to fellow entrepreneurs: Think outside the box, find innovative ways to solve problems, learn from the communities you serve, and collaborate with people who have different skills from you.

Except for Farai, who graduated earlier this year, all of them are in their final year of study. Next year, they won’t be job hunting like other new graduates. They’ll simply be stepping full time into their innovative enterprise.

An enterprise that promises to keep on sprouting and growing. And hopefully produce seeds of inspiration for other students to pick up.

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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