Name
Title | ||
|---|---|---|
Towards a dynamic model of pulmonary parenchymal deformation: evaluation of methods for temporal reparameterization of lung data |
Abstract | ||
|---|---|---|
We approach the problem of temporal reparameterization of dynamic sequences of lung MR images. In earlier work, we employed capacity-based reparameterization to co-register temporal sequences of 2-D coronal images of the human lungs. Here, we extend that work to the evaluation of a ventilator-acquired 3-D dataset from a normal mouse. Reparameterization according to both deformation and lung volume is evaluated. Both measures provide results that closely approximate normal physiological behavior, as judged from the original data. Our ultimate goal is to be able to characterize normal parenchymal biomechanics over a population of healthy individuals, and to use this statistical model to evaluate lung deformation under various pathological states. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11566489_41 | MICCAI (2) |
Keywords | Field | DocType |
statistical model | Population,Pattern recognition,Lung,Computer science,Lung volumes,Artificial intelligence,Statistical model,Deformation (mechanics) | Conference |
Volume | Issue | ISSN |
8 | Pt 2 | 0302-9743 |
ISBN | Citations | PageRank |
3-540-29326-4 | 3 | 0.58 |
References | Authors | |
6 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tessa A. Sundaram | 1 | 39 | 5.32 |
| Brian B. Avants | 2 | 2595 | 124.93 |
| James C. Gee | 3 | 4558 | 321.75 |