
This paper investigates the speckle spot detection task in ultrasound images. Speckle spots are described by structural criteria: dimensions, shape, and topology. We propose to represent the image using a morphological inclusion tree, from which speckle spots are detected using their structural appearance. This makes the method independent of contrast, and hence robusts to intensity correction. The detection was applied to speckle reduction and speckle tracking, and experiments showed that this approach performs well compared to state-of-the-art methods.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
