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Due to copyright restrictions, the access to the full text of this article is only available via subscription. Percutaneous needle procedures are mostly carried out with the guidance of 2D ultrasound (US) imaging. US images are inherently noisy and their resolutions are low. Hence, target tracking can be challenging. Image based tracking methods can be used to track the needle and the target. This paper proposes visual tracking of multiple moving points, such as biopsy needles and targets, in 2D US images using normalized cross correlation and mutual information similarity functions. Both moving and deformable targets can be tracked. An affine motion model is used for small and moving target tracking and a thin plate spline motion model is used for deformable target tracking. During the tracking, needle and target template images are updated with a template update strategy. Also, tracking outputs of normalized cross correlation and mutual information are fused using the Kalman filter to reduce the tracking error. During the experiments, needle is inserted using a needle insertion robot. 2D US probe is attached to a robotic arm's end effector to servo the probe along the needle insertion path. Proposed needle and target tracking methods were tested with phantoms. Accuracies of the needle tip and moving target tracking methods were measured using an optical tracking system. Experimental results showed that the proposed tracking method could be used to simultaneously track the needle tip and the targets in real-time in 2D US guided percutaneous needle procedures. TÜBİTAK

Due to copyright restrictions, the access to the full text of this article is only available via subscription. Ultrasound (US) is one the most commonly used medical imaging techniques in percutaneous needle procedures. However, US images are inherently noisy and contain excessive number of artifacts. Hence, it is not easy to track the needle tip in the US images during the needle insertions. At this point, image based visual tracking techniques can be used for needle tip tracking. This paper presents a method for visual tracking of biopsy needles in 2D US images using sum of squared differences and sum of conditional variances. Second order Gauss-Newton optimization is used to decrease processing time and make the tracking more robust. The needle template images used in the method are updated with a strategy to prevent needle loss and detection failures during tracking. The paper also explains how to identify needle losses during tracking and how to recover the needle position without using a needle localization algorithm. We demonstrate the precision of the visual needle tip tracking method with experiments under challenging tracking conditions. TÜBİTAK

Due to copyright restrictions, the access to the full text of this article is only available via subscription. In this paper, real-time needle tip tracking method using 2D ultrasound (US) images for robotic biopsies is presented. In this method, the needle tip is estimated with the Gabor filter based image processing algorithm, and the estimation noise is reduced with the Kalman filter. This paper also presents the needle tip tracking simulation to test accuracy of the Kalman filter under position misalignments and tissue deformations. In order to execute proposed method in real-time, the bin packing method is used and the processing time is reduced by 56%, without a GPU. The proposed method was tested in four different phantoms and water medium. The accuracy of the needle tip estimation was measured with optical tracking system, and root mean square error (RMS) of the tip position is found to be 1.17 mm. The experiments showed that the algorithm could track the needle tip in real-time. TÜBİTAK

Due to copyright restrictions, the access to the full text of this article is only available via subscription. In the percutaneous needle procedures using ultrasound (US) imaging, the needle should be detected precisely to avoid damage to the tissue and to get the samples from the appropriate site. Excessive artifacts and low resolution of the US images make it difficult to detect the needle and its tip. It is possible to enhance the needle image using image processing; and this work proposes a novel needle detection method in 2D US images based on the Gabor filter. This method enhances the needle outline while suppressing the other structures in the image. First, the needle insertion angle is estimated and then the needle trajectory is found with the RANSAC line estimator. The experiments with three different phantoms showed that the algorithm is robust and could work in percutaneous needle procedures using US images. TÜBİTAK