Abstract
The characterisation and posterior detection of speckle noise in ultrasound (US) has been regarded as an important research topic in US imaging, mainly focusing on two specific applications: improving signal to noise ratio by removing speckle noise distribution and, secondly, detecting fully developed speckle patterns in order to perform a 3D reconstruction using only image content information from freehand sensorless images. The main novelty of this work is to show that speckle detection can be improved based on finding optimally discriminant low order speckle statistics. We describe a fully automatic method for speckle detection and propose and validate a framework to be efficiently applied to real B-scan data, not being published to date. Different experiments have been carried out in order to validate the speckle detection methodology using both real and simulated data.
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