| MEDI Image Processing | Course | INF | |
|---|---|---|---|
| Lecturers : |
Prof. Dr. Thomas Schrader
eMail
|
Term | 3 |
| Course Classification : | Bachelor Medizininformatik, Katalog B-MED-INF Wahlpflicht | CH | 4 |
| Language : | Englisch | Type | VÜ |
| Type of examination : | PL | Credits | 5 |
| Method of evaluation : | written examination 120 min | ||
| Requirements : | |||
| Cross References : | |||
| Previous knowledges : | Digital signal processing | ||
| Aids and special features : | |||
| Teaching aims : | Understanding Students know the different types of images and their use in a medical context. They understand the different modalities of image generation. Analyze They can evaluate and present data from the sources mentioned. Evaluate Students can assess image data in terms of quality and content information. They are able to identify relevant information in the data. Apply They apply various image processing algorithms to improve image quality and to segment and classify (medical) images. Program algorithms in Python. Create You will be able to plan and carry out an image analysis process independently. | ||
| Contents : | Imaging procedures * Camera * Hyperspectral camera, medicine: imaging procedures in medicine (CT, X-ray, virtual microscopy) Image analysis * Histograms, grey value distributions, color spaces Image processing * Filtering, segmentation, classification Evaluation * Advanced methods of image analysis: deep learning | ||
| Literature : | Zhou SK, Greenspan H, Shen D. Deep learning for medical image analysis [Internet]. 2017 [zitiert 12. Juli 2017]. Verfügbar unter: http://public.eblib.com/choice/publicfullrecord.aspx?p=4789490 Solomon C, Breckon T. Fundamentals of digital image processing: a practical approach with examples in Matlab. Chichester, West Sussex ; Hoboken, NJ: Wiley-Blackwell; 2011. 328 S. García GB, Herausgeber. Learning image processing with OpenCV: exploit the amazing features of OpenCV to create powerful image processing applications through easy-to-follow examples. Birmingham: Packt Publ; 2015. 208 S. (Packt open source). Bovik AC. The essential guide to image processing. London ; Boston: Academic Press; 2009. 853 S. | ||