Medical Imaging Systems

Catalog description

This course introduces students to medical imaging modalities and the foundations of image processing. The fundamental concepts of physics, technology, and operation of medical imaging modalities including x-ray radiography, computed tomography, magnetic resonance imaging, and ultrasound are presented. Image acquisition and reconstruction techniques are examined alongside classical image processing methods to build the foundational knowledge necessary for medical imaging analysis. These concepts are reinforced through hands-on laboratory projects involving image acquisition, processing, and 3D printing using real and simulated medical imaging datasets. The course extends to AI-enabled image processing, where students develop foundational knowledge of deep learning architectures as applied to tasks such as image reconstruction, data augmentation, image segmentation, and classification. Through project-based learning, students implement and critically evaluate AI-enabled image processing workflows and output for clinical relevance, accuracy, and performance limitations. Applied AI Integration: This course meets or exceeds MSOE’s Applied AI Integration guidelines for substantial coverage of Practical Application and Critical Evaluation and for sufficient coverage of Foundational Knowledge.