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Misleading information was posted on a Twitter page today (17 May 2018) regarding a sexual harassment case which the former employee linked as the reason for her dismissal by the University of the Free State (UFS).
The UFS has zero tolerance towards sexual harassment, sexual assault, and the victimisation of individuals. In this particular case – which was reported on social media today – the university confirms that a sexual harassment case was indeed reported by the employee, and the university’s disciplinary process was followed. The complainant accepted the outcome of the disciplinary process without any reservations.
Sometime later, the university discovered that the complainant had falsified material information on her CV, which she used to apply for the position in which she was appointed. The termination of the complainant’s employment is based on fraudulent action and misrepresentation.
As part of its drive to eradicate fraud and corruption, the university initiated disciplinary action according to its policies and procedures.
It is unfortunate that the complainant used her sexual harassment case, which the UFS addressed to her satisfaction, to now justify her fraudulent actions.
Released by:Lacea Loader (Director: Corporate Communication and Marketing)
Telephone: +27 51 401 2584 | +27 83 645 2454
Email:
news@ufs.ac.za |
loaderl@ufs.ac.zaFax: +27 51 444 6393
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.