Cine MRI is commonly used in cardiac MR imaging and captures the motion of the myocardium throughout the cardiac cycle. Making a 3D model representation from cine MR helps to quantify clinically-relevant functional indices as well as allowing finite element models to be built from it. An example of a long axis view cardiac cine MR is shown on the right.
Using the standard open-source tools, segmenting and making a 3D model from a cine MR image is easy. However, this involves significant manual effort, and the results tend to be less than ideal. Some of the issues are:
- because the z-resolution is poorer than the in-plane resolution, segmentation leads to a jagged appearance
- short axis images lack the detail at the top and bottom of the heart, effectively truncating it
- the presence of the papillary muscles can confuse the whole process and introduces variability
- characterising the full right ventricular wall geometry is almost impossible
Despite these issues, those approaches are commonly used in research work probably because they provide the "path of least resistance". This project aims to provide a better alternative. In particular, we plan to develop an image-to-mesh generation pipeline that does not require specialist knowledge to operate, and does a decent job automatically, with the possibility for manual improvement.
In fact, this work goes far beyond the undergraduate project -- the developed algorithm will be ported into a comprehensive software platform being written currently and King's BME, for use by both clinicians and researchers. This platform is designed to integrate many different facets of research undertaken around the division into a common tool, in order to aid collaborative research.
"What will the work involve?"
There are a huge range of approaches for segmentation of cine MR (see this for a review), and probably just as many for generating a 3D mesh. We will limit ourselves to manual /semi-manual segmentation and high-order meshes in this project. Using the existing array of tools developed in-house, we will implement different mesh fitting/generation methods (high-order projection, free-form deformation, voxel-mask pre-processing, slice-based vs full 3D) and manual-correction approaches. The best algorithm will be identified by comparing to the gold standard provided by high-resolution morphological MR images.
"Is this project suitable for me?"
As with any project, the content will be tailored to the interest and strength of the student, however, in general this project will require the ability for mathematical thinking and matlab programming. The experience will be relevant for future industry or academic work.
"I'm still unclear / unsure / undecided"
If you would like more information on the project (or anything else) feel free to drop me an email and visit me. I will do my best to clarify any issues. You can also leave your questions below in the comments section.