Medical Image Data Collection & Management is a Course
Medical Image Data Collection & Management
Time limit: 56 days
4.5 credits
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Full course description
Course Introduction:
This course builds upon the foundations of Engineering in Medical Imaging in the Clinical Service Engineering certificate, to walk through the operation and implementation of medical imaging systems in a clinical environment, particularly focusing on configuring equipment, designing operational workflows, programming and networking systems, managing data through complex interfaces, and analyzing images.
Pre-requisites: Engineering in Medical Imaging 1 and 2
Learning Outcomes:
At the end of the course, students should be able to:
- Diagram, and explain using words and theory, the circuit implementation for X-Ray detectors.
- Describe common noise problems in detector systems and explain the root cause and solutions for each.
- Demonstrate the appropriate use of noise reduction techniques for a given noise problem.
- Explain, using words and diagrams, the various networking methods used to connect and transfer medical image data from or between medical imaging systems and workstations.
- Demonstrate how to correctly network imaging systems using Windows Server and DICOM.
- Explain, using words and diagrams, the overarching image process and analysis framework through which medical images are acquired and reviewed.
- Describe, using words, diagrams, and theory, the primary types of image/video processing and analysis methods, how they function, and how they relate to each other.
Module Topics:
Modules include:
• Noise
• Noise Sources & Mechanisms
• Networking Basics
• Linux Operating System
• Medical Image Processing
• MATLAB for Medical Image Processing
• Introduction to medical images
• Image segmentation
• Image registration
Instructor: Prof. Changyu Sun
MU Extension Contacts: Sarah Rielley and Jonathan Mack
Length:
8 weeks
Department:
Biomedical, Biological, and Chemical Engineering
Credit:
45 continuing education hours (4.5 continuing education units); no academic credit
Audience:
Non-traditional students