Name
Abstract | ||
|---|---|---|
We address the task of aortic diameter measurement in (non-contrast-enhanced) plain axial cardiac cine MRI. To this end, we set up a likelihood maximization problem which allows us to recover globally optimal aorta locations and diameters of the cine sequence efficiently. Our approach provides intuitive means of manual post-correction and requires little user interaction, making large-scale image analysis feasible. Experiments on a data set of 20 cine sequences with 30 time frames showed (at least) pixel-accurate diameter measurements which are also highly stable against re-parameterization. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-662-46224-9_51 | BILDVERARBEITUNG FUR DIE MEDIZIN 2015: ALGORITHMEN - SYSTEME - ANWENDUNGEN |
DocType | Citations | PageRank |
Conference | 1 | 0.48 |
References | Authors | |
2 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marko Rak | 1 | 1 | 0.48 |
| Alena-Kathrin Schnurr | 2 | 1 | 0.48 |
| Julian Alpers | 3 | 1 | 0.48 |
| Klaus-Dietz Tönnies | 4 | 2 | 3.87 |