Abstract
The registration of 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 treatment effectiveness, which are essential for deciding on the most appropriate therapeutic plan. Aggressive research has led to considerable progress in image registration for CT, MR, and PET. However, due to various factors peculiar to the ultrasound modality, there have been far fewer research studies on image registration focusing on ultrasound than on other modalities. Recently, diagnostic ultrasound systems that can acquire and record three-dimensional volume data continuously have been developed. In ultrasound diagnostics, it is extremely important to be able to reliably match positions for a series of images obtained at various stages of the diagnostic and treatment processes. This has led to strong demand for a reliable image registration technique. We have proposed a unique registration technique using volume similarity measures based on multi-small regional mutual information and have demonstrated its effectiveness. In order to apply this technique in the clinical setting, it is necessary to improve its processing speed. The present study introduces a computational acceleration method for our registration technique which employs a graphics processing unit (GPU). The results indicate that it may be possible to increase the processing speed by a factor of 30 or more.
