Name
Abstract | ||
|---|---|---|
This work aims at detecting cardiac cavities in 2D echocardiographic sequences. In this respect, we propose to extend to the case of moving images, a competitive fully automatic intraframe segmentation method. The latter handles the spatial information by characterizing the texture in each image and, involves the watershed algorithm using an optimal texture gradient image and a suitable seeds image. The novelty of our work consists in accounting for the dynamic evolution according to two strategies. The first one consists in projecting and refining the boundaries from a frame to the next one. The second strategy acts on the inputs of the watershed algorithm. Experiments are carried out on apical 2D-echocardiographic sequences and, they show the benefit that can be drawn from the proposed strategies in terms of both objective accuracy metrics and computational complexity. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ISIVC.2018.8709183 | 2018 9th International Symposium on Signal, Image, Video and Communications (ISIVC) |
Keywords | Field | DocType |
Echocardiographic images,texture descriptors,watershed segmentation,seeds image,motion estimation | Spatial analysis,Computer vision,Computer science,Segmentation,Image segmentation,Watershed,Artificial intelligence,Novelty,Ultrasonic imaging,Computational complexity theory,Ultrasound | Conference |
ISBN | Citations | PageRank |
978-1-5386-8174-9 | 0 | 0.34 |
References | Authors | |
12 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| d attia | 1 | 3 | 1.68 |
| Amel Benazza-Benyahia | 2 | 271 | 32.72 |