Dr. Dona Lemus earned her M.Sc. degree in Medical Physics and Applied Radiation Sciences and PhD degree in Biomedical Engineering at McMaster University, Canada; specializing in Magnetic Resonance Imaging (MRI) applications. She then continued her training as a postdoctoral fellow at Sunnybrook Research Institute, Canada working on MRI-guided Ultrasound-Stimulated Microbubbles Therapy to enhance the efficacy of radiation therapy. Subsequently, she completed her medical physics residency training at Columbia University Vagelos College of Physicians and Surgeons, New York where she worked on different deep learning applications towards on-line adaptive radiation therapy.
Dr. Dona Lemus is broadly interested in image processing and image analysis with particular interest in the medical images used for radiation therapy treatment planning and image guided treatments. Her research interests are shaped by the emerging trends towards deep learning systems that enable personalized medicine and adaptive planning.
Currently, her research focuses on generating high quality synthetic narrow beam computed tomography images from low quality cone beam computed tomography images to enable fast and accurate dose calculation. Additionally, she is exploring the feasibility of using cycle consistent generative adversarial networks to create virtual exogenous contrast on synthetic images with the end goal of enhancing the target volume for daily adaptive radiation therapy.