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Prof Tameshnie Deane appointed as Vice-Dean in the Faculty of Law

17 October 2024 | Story Anthony Mthembu | Photo Supplied

The Faculty of Law at the University of the Free State (UFS) has appointed Prof Tameshnie Deane as Vice-Dean: Research, Postgraduate Studies and Internationalisation. Prof Deane officially assumed this role on 1 July 2024, following over two decades as a Professor and Head of the Criminal Law Unit at the University of South Africa (UNISA).

Prof Deane, who has approached this new position with great enthusiasm, describes it as a significant opportunity. ‘’This role allows me to influence the future of academic research and postgraduate education at UFS,’’ she said.

Support for postgraduate students

Prof Deane elaborated on her vision, saying, “My aim is to develop and implement strategies that elevate the quality and impact of research, foster innovation, and support postgraduate students in achieving their academic and professional goals.”

Among her top priorities is strengthening support for postgraduate students at the UFS. “I plan to introduce comprehensive mentorship programmes where experienced faculty members guide students through their academic and research journeys. We will offer training in key skills such as legal writing, research methodologies, and public speaking, while also prioritising initiatives to support their mental and emotional well-being,’’ she explained.

Prof Deane emphasised that creating a dynamic and supportive environment will contribute to academic excellence and personal growth for postgraduate students at the UFS.

Enhancing internationalisation and strategic collaborations

Prof Deane is also committed to advancing the internationalisation of the Faculty of Law. “We aim to provide opportunities for international collaboration and exchange, which will broaden the scope and impact of our research and postgraduate programmes,’’ she said.

Improving research quality and output remains a core objective, with Prof Deane identifying this as central to her new role.

One of the initiatives Prof Deane is eager to lead is the development of strategic partnerships with industry and academic institutions. “Collaborations like these will provide invaluable resources for research projects,” she noted.

To foster these partnerships, Prof Deane plans to leverage technology to strengthen communication and collaboration, support relationship-building events, and promote interdisciplinary projects that encourage diverse perspectives and innovative solutions.

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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