Ischemic Segment Detection using the Support Vector Domain Description |
|
| Abstract | Myocardial perfusion Magnetic Resonance (MR) imaging has proven to
be a powerful method to assess coronary artery diseases. The
current work presents a novel approach to the analysis of
registered sequences of myocardial perfusion MR images.
A previously reported AAM-based segmentation and registration of
the myocardium provided pixel-wise signal intensity curves that
were analyzed using the Support Vector Domain Description (SVDD).
In contrast to normal SVDD, the entire regularization path was
calculated and used to calculate a generalized distance. The
results corresponded well to the ischemic segments found by
assessment of the three common perfusion parameters; maximum
upslope, peak and time-to-peak obtained pixel-wise. |
| Type | Conference paper [With referee] |
| Conference | International Symposium on Medical Imaging |
| Editors | The International Society for Optical Engineering (SPIE) |
| Year | 2007 Month February |
| BibTeX data | [bibtex] |
| IMM Group(s) | Image Analysis & Computer Graphics |