Name
Title | ||
|---|---|---|
A framework for the merging of pre-existing and correspondenceless 3D statistical shape models. |
Abstract | ||
|---|---|---|
•A new framework for the normalization and merging of pre-existing PDMs.•The framework handles different shape topologies, and training populations.•Variability of PDMs can be combined without the need for the original raw data.•Results demonstrate the accuracy and potential of the approach for segmentation. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.media.2014.05.009 | Medical Image Analysis |
Keywords | Field | DocType |
Statistical shape model,Point distribution model,Eigenspace fusion,Point correspondence,Image segmentation | Active shape model,Computer vision,Point distribution model,Normalization (statistics),Parametrization,Pattern recognition,Medical imaging,Image segmentation,Artificial intelligence,Statistical model,Mathematics,Encoding (memory) | Journal |
Volume | Issue | ISSN |
18 | 7 | 1361-8415 |
Citations | PageRank | References |
6 | 0.47 | 39 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marco Pereañez | 1 | 31 | 6.77 |
| Karim Lekadir | 2 | 199 | 17.68 |
| Constantine Butakoff | 3 | 336 | 32.52 |
| Corné Hoogendoorn | 4 | 73 | 9.80 |
| Alejandro F. Frangi | 5 | 4333 | 309.21 |