This Course Aims to Equip Students With The Essential Skills And Knowledge Required For Proficient Medical Image Analysis Using Deep Learning Techniques. Students Will Be Introduced to The Core Concepts Of Deep Learning and How They Can Be Effectively Applied to Various Aspects of Medical Imaging Analysis, Including Image Classification, Segmentation, and Registration. Specifically, The Course Will Delve Into Convolutional Neural Networks (cnns), Transformer Models With Attention Mechanisms, Long Short-term Memory (lstm) Networks, Loss Functions Suitable For Medical Image Analysis, Data Augmentation Techniques For Enhancing Model Generalization and Robustness, As Well As Uncertainty Estimation Methods For Quantifying Model Confidence And Reliability. Hands-on Experience With Pytorch Will Be Emphasized Through Tutorials and Practical Exercises. Learning Outcomes# at The End of The Course The Students Will Be Able To# 1. Develop Proficiency in Medical Image Analysis With Deep Learning, Leveraging Pytorch For Effective Implementation. 2. Apply a Variety of Deep Learning Techniques, Including Cnns, Transformers, and Lstms, to Address Diverse Medical Image Analysis Tasks. 3. Develop and Implement Loss Functions Suitable For Medical Image Analysis Tasks. 3. Develop and Implement Loss Functions Suitable For Medical Image Analysis Tasks. 4. Enhance Model Robustness and Generalization Through The Application Of Data Augmentation Techniques Tailored For Medical Imaging Datasets. 5. Assess Model Confidence and Reliability Using Uncertainty Estimation Methods, Ensuring Transparent and Accountable Decision-making in Clinical Settings.

Faculty: Biomedical Engineering
|Undergraduate Studies |Graduate Studies
Pre-required courses

(46195 - Machine Learning and 46200 - Image Processing and Analysis and 236756 - Introduction to Machine Learning and 236860 - Digital Image Processing and 336027 - Medical Image Processing and 336207 - Medical Image Processing and 336546 - Machine Learning in Healthcare)

Course with no extra credit (contains)

236781 - Deep Learning On Computation