Respiratory Compensation in Contrast Enhanced Ultrasound Using Image Clustering

摘要

Image acquired during free breathing using contrast enhanced ultrasound (CEUS) hepatic perfusion imaging exhibits a periodic motion pattern. It needs to be compensated for if a further accurate quantification of the hepatic perfusion analysis is to be executed. A respiratory motion compensation strategy for CEUS imaging by using image clustering is proposed in this work. The proposed strategy separated the dual mode image to tissue image and contrast image firstly. Then, the image subsequences based on the tissue image are determined by using sparse subspace clustering (SSC) method. Finally, the motion compensated contrast images are acquired by using the position mapping. The strategy was tested on ten CEUS hepatic perfusion image sequences. Quantitative and visual comparisons demonstrate that the proposed strategy can compensate the misalignment of ultrasound hepatic perfusion image sequence caused by respiratory motion in free-breathing.