Fusion of multi-modal cardiac data
Master's thesis and projects
The Department of circulation and medical imaging offers projects and master's thesis topics for technology students of most of the different technical study programmes at NTNU. There is a seperate page for the supplementary specialisation courses.
List of topics
Topics for thesis and projects are given below. Most of the topics can be adjusted to the students qualifications and wishes.
Don't hesitate to take contact with the corresponding supervisor - we're looking forward to a discussion with you!
Fusion of multi-modal cardiac data
Full 3D datasets of the heart can be acquired using different imaging modalities e.g. 3D echocardiography (3D echo), computed tomography (CT) and cardiac magnetic resonance imaging (CMR). Using image fusion the strengths of different image modalities can be combined. As such, by co-registering multi-modal datasets, a direct spatial relationship between anatomical and functional information in the underlying data is established and visualized.Furthermore in the case of 3D echo the image quality has large variations between subjects, the spatial resolution varies with depth and the tissue contrast is angle dependent. One possibility of improving image to noise ratio and to extend the field of view is to acquire multiple datasets from different angles, detect corresponding features in each view and fuse the recordings in order to generate a combined volume.
The aim of the project is to develop fusion and image registration techniques to combine multiple 3D cardiac acquisitions with the goal of improving signal-to-noise ratio, spatial resolution and field of view or to improve the diagnostic process and to demonstrate their applicability during live scanning.
Project topics:
- Test/adapt state of the art image registration algorithms on ultrasound and CMR data
- ECG based temporal synchronization of data
- Comparison of various fusion algorithms vs the quality of the resulting image data
Skills (dependent on the project):
- Knowledge of Python, Matlab and/or C++ programming
- Desire to learn parallel computing (CUDA or OpenCL)