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18 April 2019 | Story Rulanzen Martin

The Institute for Reconciliation and Social Justice IRSJ) has initiated a Social Justice Week at the University of the Free State (UFS), which started on Friday 12 April  until Wednesday 17 April 2019. 

Ten key events took place during the week. It ranged from dialogues, workshops, talk shows, debates, and interactive displays and events on issues of multilingualism and diversity, social innovation, engaged scholarship, the Fourth Industrial Revolution, gender sensitisation, sexual consent, sexual preparedness, universal access, disability, anti-discrimination, and security.

There was also a round-table discussion on 17 April 2019 with various UFS stakeholders on off-campus student security as well as an inter-institutional discussion on the same topic. The UFS Debating Society will take on the topic of the UFS Language Policy, while Olga Barends from the Free State Centre for Human Rights will host a dialogue on sexual consent.

The IRSJ has also designed and implemented SOJO-VATION: Social Innovation/ Social Change, which strives to create a foundational platform where ideas of social justice, innovation, and engaged scholarship at the UFS and in society can be hosted. SOJO-VATION partners with the Office for Student Leadership, Development, and Community Engagement.

The collaborating partners for the Social Justice Week includes various UFS stakeholders such as the Sasol library, the Gender and Sexual Equity Office, UFS Protection Services, the Free State Centre for Human Rights, the Student Representative Council (SRC), the Office for Student Leadership Development, Kovsie Innovation, GALA, the FFree State Centre for Human Rights, SRC Associations, the Office for Student Governance, Kovsie Innovate, Start-Up-Grind, EVC, EBL, Community Engagement, the Institutional Transformation Plan (ITP) Dialogues Office, Residence Dialogues, UFS Debating Society, Debate Afrika!, the Center for Universal Access and Disability Support (CUADS), and the Gateway Office. 

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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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