University of Iowa 3 credits BME
Overview of deep learning architectures related to medical image analysis, including convolutional neural networks, auto-encoders, generative adversarial networks, and transformers; solve challenging medical imaging problems using image diagnosis, detection, segmentation, registration, and synthesis; use Python libraries including PyTorch, MONAI, SimpleITK, NumPy, and Matplotlib. Prerequisites: ENGR:2730. Requirements: practical knowledge of programming. Recommendations: ECE:5480, proficiency in Python, and comfortable with calculus, matrix algebra, and basic probability and statistics.
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