I am Isuru Wijesinghe, a postdoctoral researcher at the King’s College London, School of Biomedical Engineering & Imaging Sciences. My primary research interests lie in the areas of medical image analysis through deep learning in particular classification, segmentation, content-based image retrieval, image reconstruction, and motion modelling in adaptive radiotherapy. My research at King’s is to develop and analytically validate an AI tool for automatic triaging of portable ultra-low-field MRI brain scans of adult patients for the purposes of triage. I recently completed my PhD at the University of Leeds, where I focused on developing intelligent, image-driven motion modelling techniques for adaptive radiotherapy. My research involved creating patient-specific, deep learning-based methods to estimate internal anatomical motion using a single kV planar X-ray image acquired from any arbitrary projection angle. This work required extensive handling of complex 3D and 4D CT/CBCT datasets and aimed to enhance the precision of radiation dose delivery, improving accuracy in targeting tumours while minimising exposure to nearby sensitive tissues. I hold a Master of Science degree (with a major component in research) in Engineering, specializing in Medical Image Analysis through Deep Learning from the University of Moratuwa. In addition, I earned a Bachelor of Science (Honours) degree in Engineering, with a specialization in Computer Science and Engineering, also from the University of Moratuwa.

During my MSc research, I developed a predictive model to classify the severity levels of Diabetic Retinopathy using retinal images, employing an ensemble of deep convolutional neural networks (CNNs). I subsequently extended this classification model into a content-based image retrieval architecture, enabling the search for retinal images with characteristics similar to the cases of interest. Furthermore, I have participated in two collaborative research projects: one focused on detecting wound boundaries in diabetic patients using deep learning, and the other aimed at classifying anomalies in the gastrointestinal tract through endoscopic imagery with deep learning techniques. Prior to commencing my MSc studies, I gained valuable experience in the software industry. I completed my undergraduate internship at Sysco LABS (Pvt) Ltd, and subsequently worked for WSO2 Lanka (Pvt) Ltd, where I held the positions of Software Engineer for one year and Senior Software Engineer for an additional year. Following that, I joined Linear Squared (Pvt) Ltd as a Senior Data Engineer, where I worked for one year.