Prior shape information has been shown to be invaluable for segmenting cardiac boundaries. We develop new methods of exploiting such prior information to guide the segmentation by using techniques of machine learning or formulating the segmentation problem to fit our requirements in segmentation of 4D cardiac data. In this project, in collaboration with the German Heart Center in Munich, new methods for accurate are provided and applied to heart images from different moralities.
Requirements
Knowledge of Basics of medical image processing
Knowledge of programming in Matlab/C++
What do we offer
Experience with different fields of research in cardiac image analysis.
Knowledge about clinical medical technologies.
Your thesis and degree. (and also an academic paper, which depends on your performance)
Working within the real project on the cutting edge technology.
Prior shape information has been shown to be invaluable for segmenting cardiac boundaries. We develop new methods of exploiting such prior information to guide the segmentation by using techniques of machine learning or formulating the segmentation problem to fit our requirements in segmentation of 4D cardiac data. In this project, in collaboration with the German Heart Center in Munich, new methods for accurate are provided and applied to heart images from different moralities.
