Experimental Evaluation of Needle Tip Prediction Using Kalman Filtering Approach

In both manual and autonomous needle steering procedures involved in percutaneous interventions, target reaching accuracy depends on feedback of the actual needle tip position through imaging feedback modalities such as CT, MRI, and US. For online analysis, US imaging modality is preferred compared to others. In this article, we propose a linear Kalman filtering based online prediction of a brachytherapy needle using US imaging modality. Extensive experimental studies were performed to confirm the accuracy of the needle prediction in both artificial and biological tissues. From the results, we show that the proposed methodology gives clinically acceptable outcomes as we compare with the standard electromagnetic (EM) sensory feedback values of the needle tip position.