Gabor-based needle detection and tracking in three-dimensional ultrasound data volumes

During needle interventions for e.g. regional anaesthesia or biopsy, it is very important to visualize the needle and its tip with respect to important structures in the body. In this work, we propose a novel image-based needle detection technique in a 3D ultrasound volume dataset, which can improve the intervention. We present a novel application of the 3D Gabor transformation, which exploits needle-like structures with appropriate designs. Furthermore, we introduce a needle tracking algorithm based on Gradient Descent and show that it limits the computational complexity and detection error. Finally, we visualize the needle on 2D cross-sections of the volume in order to be presented to the physician. Evaluation of our system in challenging cases shows a high detection score (up to 100% but needs larger sets) and accurate visualization.