Automatic Ultrasound Image Registration by Multi-Small Regional Mutual Information

Abstract

Image registration for ultrasound images acquired at different stages of diagnosis and treatment is extremely important. Reliable image registration facilitates the monitoring of tumors over time and the evaluation of therapeutic effectiveness, which are essential for determining the most appropriate course of treatment. Aggressive research has led to considerable progress in image registration methods for CT, MR, and PET. However, due to various factors peculiar to the ultrasound modality, there have been significantly fewer image registration research studies on ultrasound than other modalities. Due to the mutual information calculation algorithm, the increases (or decreases) in mutual information of sub-regions do not necessarily reflect the increase (or decrease) in mutual information of the combined entire region. To address this point, we previously proposed an effective ultrasound image registration method employing the unified mutual information derived from a few multiple small regions. However, these regions were set in morphological information-rich areas by operator action. In order to improve consistency and reproducibility, we now propose an automatic VOI placement method in which a comparatively large number of VOIs are set at the center of the image. We have evaluated the effectiveness of the proposed method using clinical data and have confirmed that it can provide the same level of registration performance as manual VOI setting.