Name
Title | ||
|---|---|---|
Iteratively Learning A Liver Segmentation Using Probabilistic Atlases: Preliminary Results |
Abstract | ||
|---|---|---|
This works deals with the concept of liver segmentation by using a priori information based on probabilistic atlases and segmentation learning based of previous steps. A probabilistic atlas is here understood as a probability or membership map that tells how likely is that a point belongs to a shape drawn from the shape distribution at hand. We devise a procedure to segment Perfusion Magnetic Resonance liver images that combines both: a probabilistic atlas of the liver and a segmentation algorithm based on global information of previous simpler segmentation steps, local information from close segmented slices and finally a mathematical morphology procedure, namely viscous reconstruction, to fill the shape. Preliminary results of the algorithm are provided. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICMLA.2016.194 | 2016 15TH IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA 2016) |
Keywords | Field | DocType |
liver segmentation, probabilistic atlas, viscous reconstruction | Scale-space segmentation,Computer science,A priori and a posteriori,Segmentation-based object categorization,Image segmentation,Artificial intelligence,Probabilistic logic,Iterative reconstruction,Computer vision,Pattern recognition,Segmentation,Mathematical morphology,Machine learning | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Juan Domingo | 1 | 3319 | 258.54 |
| Esther Dura | 2 | 8 | 3.60 |
| Evgin Göçeri | 3 | 9 | 2.50 |