Beamforming techniques for ultrasound microcalcification detection

Evaluation of microcalcifications helps early detection of breast cancer and classification of benign and malignant masses. Though ultrasound is a proven adjunct to mammography, especially in dense breast tissue, its sensitivity to microcalcifications is usually poor. To enable early ultrasound-based cancer detection in dense breast, the sensitivity has to be improved. Here we report beamforming techniques for imaging microcalcifications. The strategy is to involve channel-data-based parameters that favor point/sub-resolution targets, which microcalcifications resemble acoustically. Accordingly, we have devised algorithms based on coherence factor and dominance of the first eigenvalue of covariance matrices. The two parameters are used to derive a binary microcalcification map. The initial results based on in vivo and phantom data show potential of the proposed techniques for microcalcification detection.

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