Faculty of Medicine and Dentistry
The course will cover applications of Machine Learning (ML) in medical imaging modalities like ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI) that are commonly used in Radiology. Starting with a brief introduction to Artificial Intelligence and ML, this course will cover the perceptron model, multilayer perceptron (MLP), convolutional neural networks (CNN), recurrent neural networks (RNN), transformers, autoencoders, and generative models (like GANs). Image classification models, semantic segmentation models, and instance segmentation models used in medical image datasets will be discussed. This course is intended for graduate students in Radiology, Biomedical Engineering, and other relevant disciplines whose research interests are related to the use of Machine Learning (ML) techniques in medical imaging.