Medical Image Analysis (Sommersemester 2015)
News
07.04.15 |
Herzlich Willkommen zur Vorlesung Medical Image Analysis im Sommersemester 2015. An dieser Stelle werden aktuelle Informationen zur Vorlesung bereitgestellt. Allgemeine Informationen und Materialen zur Vorlesung finden Sie weiter unten auf der Seite. |
18.05.15 |
NÄCHSTE VORLESUNG 21.05.2015 um 16:00 ct in M4. |
Contents
Medical Imaging allows to gain information about the inner condition of the patients without or with minimal surgery. This information is helpful in the diagnosis and treatment. Different imaging techniques, such as X-Ray, CT, MRI, PET, Ultrasound, are being used for this purpose today. The special requirements and the process of image acquisition vary from technique to technique. This necessitates specially adapted solutions for image analysis. Medical image analysis has become an important part of computer science and computer vision. In this series of lectures, different medical imaging modalities will be described and the process of image formation explained. Also, methods of image reconstruction, registration, segmentation, motion correction and classification will be presented. Some problems of medical image analysis will be discussed and exercises based on methods from medical image processing will be used to solve them.
Materials
Lecture 01 |
Basics of Image Processing-1: Grayscale Transformations / Color spaces / Fourier Transform / Point operations / Neighbourhood operations |
Lecture 02 |
Basics of Image Processing-2: Edge detection / Hough Transformation / Morphological operations |
Lecture 03 |
Modalities-1: X-Ray / CT / MRT |
Lecture 04 |
Modalities-2: Basics of Radioactive decay / Gamma-Ray Scintigraphy / SPECT / PET |
Lecture 05 |
Modalities-3 / Reconstruction: Ultrasound / Radon Transform / Filtered Back Projection / ART |
Lecture 06 |
Registration: Rigid / Affine registration / PCA / SVD / Iterative Closest Point / RANSAC / Distance Measures / Optical Flow Algorithms |
Lecture 07 |
Segmentation: Threshold Based Segmentation/Clustering Methods/Region Growing/Watersheds |
Information