Dr Rahele Kafieh



I received a BSc (2005) followed by an MSc (2008) and a Ph.D. (2014) in Biomedical Engineering from Sahand University of Technology and Isfahan University of Medical Sciences in Iran. I obtained my first tenure post as an assistant professor in the Department of Advanced Technologies in Medicine at Isfahan University of Medical Sciences in 2014, and remained there for 7 years, during which I obtained valuable experience in teaching and supervision of projects at the undergraduate and graduate levels. My research in Iran was focused on machine learning for biomedical image processing through close collaboration with clinicians. I have led many successful previously-unexplored projects on medical images, including but not limited to classification and segmentation of retinal images with AI; applications of AI in CT-scan and X-ray images; and multi-modality MRI data analysis.

My two stays at Charité university hospital, Germany, and one stay at Sabanci University in Turkey were awarded by competitive research scholarships from the Einstein forum and TUBITAK, respectively. They provided me with the opportunity for face-to-face international collaborations and the invaluable experience of living abroad. At Charité, I designed AI algorithms for ocular images. The research output was highly practical and trustworthy and is currently in operation in clinical research. The work in Sabanci, on the other hand, was mostly focused on mathematical aspects and yielded to the introduction of a new image transformation.

I then moved to Newcastle University, where I worked as a Research Associate in an interdisciplinary team at Newcastle University, a position that provided me the great opportunity to conduct in-depth research on the role of artificial intelligence (AI) in the detection of neurological diseases from the eye. Since July 2022, I have been with the Department of Engineering at Durham University as an Assistant Professor.

My current research is on medical image processing and I had leadership positions in multiple projects for pre-processing, segmentation, and classification of data from different organs (eye, chest, teeth, brain, heart, breast), from different modalities (OCT, Fundoscopy, CT-scan, X-ray, cone-beam CT, MRI, fMRI, and infrared), facing challenges like high dimensionality, noisiness, and imbalance. 

 




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