Alejandro is a master’s student in the biomedical engineering graduate program at the University of Calgary. He is currently working in the Medical Image Processing and Machine Learning Laboratory under supervision of Dr. Nils D. Forkert. Alejandro investigates state-of-the-art deep learning-based data augmentation methods to overcome the problem of image data scarcity in many neuroscientific studies.
Artificial intelligence has increasingly shown great potential to identify disease patterns within medical images. However, to achieve good results, these methods typically require large amounts of images. Acquiring enough medical images for these studies is an often long and costly process. My project aims to not only alleviate the problem of image data scarcity for neuroscientific studies, but also to provide a solution that is more accessible for research teams. This will be achieved by developing a general open- source framework that automatically generates artificial but realistic images using only a few real datasets to learn from.
Check out Alejandro’s presentation of his CONP project in a short talk entitled “Data augmentation through generative modelling on brain-image data“.