Target detection in diagnostic ultrasound: Evaluation of a method based on the CLEAN algorithm

A technique is proposed for the detection of abnormalities (targets) in ultrasound images using little or no a priori information and requiring little operator intervention. The scheme is a combination of the CLEAN algorithm, originally proposed for radio astronomy, and constant false alarm rate (CFAR) processing, as developed for use in radar systems. The CLEAN algorithm identifies areas in the ultrasound image that stand out above a threshold in relation to the background; CFAR techniques allow for an adaptive, semi-automated, selection of the threshold. Neither appears to have been previously used for target detection in ultrasound images and never together in any context. As a first step towards assessing the potential of this method we used a widely used method of simulating B-mode images (Field II). We assumed the use of a 256 element linear array operating at 3.0 MHz into a water-like medium containing a density of point scatterers sufficient to simulate a background of fully developed speckle. Spherical targets with diameters ranging from 0.25 to 6.0 mm and contrasts ranging from 0 to 12 dB relative to the background were used as test objects. Using a contrast-detail analysis, the probability of detection curves indicate these targets can be consistently detected within a speckle background. Our results indicate that the method has considerable promise for the semi-automated detection of abnormalities with diameters greater than a few millimeters, depending on the contrast.

► Semi-automated ultrasound image target detection method proposed and evaluated.
► Uses the CLEAN algorithm in combination with an adaptive form of CFAR.
► Performance evaluated using B-mode linear array image simulations using FIELD II.
► Evaluations based on targets with diameters ranging from 0.25 to 6 mm.
► Method shows considerable promise for semi-automated detection of abnormalities.