CSCI 8355 Deep Learning Algorithms for Medical Imaging
This PhD-level course explores deep learning algorithms with a focus on applications in medical imaging. The course is organized into four parts: Foundations – introduction to foundational concepts in deep learning and medical imaging, including regression models, convolutional neural networks, and transformers, etc. Implementation – hands-on training in PyTorch, with in class coding assignments that build and evaluate key architectures. Critical Reading – discussion of seminal and state-of-the-art research papers in medical imaging. Research Project – a semester-long research project culminating in a conference-style presentation and manuscript submission.
By the end of the course, students will gain theoretical knowledge, practical coding experience, and research skills necessary to advance the field of deep learning in medical imaging.