Detecting bladder and pelvic floor motion during MRI using a small ultrasound-based sensor

Deep-seated motion due to digestion and bladder filling can be difficult to monitor during MR acquisition. In this study, we use a small ultrasound-based sensor to detect bladder and pelvic floor motion, with a real-time MRI acquisition and a pilot-tone motion-sensitive signal as a reference. A neural network is used to predict the bladder area at various times during the MRI scan by using the US signal features. Our results indicate that the correlations between the ultrasound sensor and the MRI are beneficial for detecting bladder motion over time.