Name
Title | ||
|---|---|---|
How to fix any 3D segmentation interactively via Image Foresting Transform and its use in MRI brain segmentation |
Abstract | ||
|---|---|---|
In medical imaging, there are many approaches for automatic segmentation. However, none of these methods provide any effective solution to correct segmentation interactively, which becomes a necessity in the case of poorly defined structures. Manual segmentation can not be an alternative given that it might be unfeasible in many cases. On the other hand, how to complete a poor automatic segmentation in an interactive tool is an issue, since the automatic approach and the tool may have been designed with different optimization criteria. We propose solutions to this problem using the framework of the “Image Foresting Transform” (IFT), with evaluation in the context of the segmentation of MR-T1 brain structures. The results indicate that effective semi-automatic correction is possible using just a few markers. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ISBI.2011.5872811 | Chicago, IL |
Keywords | Field | DocType |
biomedical MRI,brain,image segmentation,medical image processing,neurophysiology,optimisation,3D segmentation,MRI brain segmentation,image foresting transform,optimization,semiautomatic correction,MR-image segmentation,image foresting transform,medical image processing,robustness in image segmentation | Brain segmentation,Computer vision,Scale-space segmentation,Pattern recognition,Computer science,Segmentation,Medical imaging,Segmentation-based object categorization,Image segmentation,Robustness (computer science),Artificial intelligence | Conference |
ISSN | ISBN | Citations |
1945-7928 E-ISBN : 978-1-4244-4128-0 | 978-1-4244-4128-0 | 7 |
PageRank | References | Authors |
0.46 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paulo A. V. Vechiatto Miranda | 1 | 313 | 26.26 |
| Alexandre X. Falcão | 2 | 1877 | 132.30 |
| Guilherme C. S. Ruppert | 3 | 34 | 4.01 |
| Fabio A. M. Cappabianco | 4 | 19 | 1.48 |