Accurate image registration using SIFT for extended-field-of-view sonography

Extended-field-of-view (EFOV) sonography has been proven to be capable of illustrating panoramic ultrasound images. In EFOV technology, accurate registration of original images is the basis. Conventional registration methods based on block matching cannot provide adequate accuracy when the relative rotations among the images are large. To register the images with improved accuracy, this paper proposes a novel methodological framework based on SIFT (Scale Invariant Feature Transform) and Levenberg-Marquardt (L-M) algorithms to obtain the transforming matrices. The SIFT is used to detect plenty of distinctive invariant features which can be used for reliable matching between the images with overlapping regions. After obtaining a series of pairwise matching points, we use the L-M algorithm, a non-linear optimization, to obtain the translation and rotation parameters between two adjacent images. Using the parameters, any pair of two adjacent images can be transformed into one coordinate system to generate a panorama. Preliminary experiments have been performed and the effectiveness of our approach is demonstrated.