Image Processing in Medicine
Generation, processing, and analysis of image data for medical applications
Faculty of Engineering and Health, University of Applied Sciences and Arts Hildesheim/Holzminden/Göttingen (HAWK)
Today, medical imaging science (e.g. radiology, photonics) is a dynamic, evolving field generating a wealth of data in medicine. Major trends are functional, multimodal, molecular and intraoperative imaging. Advanced algorithms and image-analysis methods can be used to enhance images and extract novel information for medical diagnosis and therapy. If they are to be used in clinical decisions, both the strengths and limitations of generating such images must be understood.
Target Group: The module is oriented to Bachelor's level. The course is aimed at Bachelor’s students of medical engineering and medical informatics, as well as IT-savvy physicians and medical students. Basic knowledge in applied mathematics, engineering, and applied computer science, e.g. programming knowledge, is required.
Learning Objectives: The course offers its participants an introduction to the methodology of processing and analyzing medical image data, using computer-aided methods with the focus on imaging modalities, image representation and storage, image preprocessing and enhancement, image segmentation, feature detection, and basic classification. Additionally, the consideration of quality measures including sensitivity and the specificity of image-based diagnostic testing forms an essential part of the course. Practical exercises and interactive examples are provided to deepen the knowledge in individual and group work, using common software tools and libraries.
Embedding: The scope of the module comprises 6 credit points at the HAWK. The module serves as a foundation for the understanding of advanced image processing concepts such as classification and object recognition, e.g. methods based on machine learning covered by other modules.