Gabor filter-based localization of straight and curved needles in 2D ultrasound images

Abstract

2D ultrasound (US) is one of the most commonly used medical imaging devices for needle localization in biopsies. However, the produced images are low-resolution and contain an excessive number of artifacts, which makes the needle localization challenging. Image processing techniques can help resolve this issue. This paper presents a novel Gabor filter-based method for needle localization in 2D US images, which enhances the needle outline in the images while suppressing other structures. The scheme works in two stages: First, the Gabor filter is applied to the image, the needle insertion angle is estimated, and the needle trajectory is found using a RANSAC line fitting; then, the Gabor filter is repeated using the estimated insertion angle and the location of the needle tip is estimated using probability mapping. The proposed scheme works with both straight and curved needles. An automatic parameter tuning method, which is used to optimize the threshold value of the Otsu's method, is also presented here. The tests on this needle localization scheme were done using two different water mixtures, three different gelatin-based phantoms, and ex vivo experiments. The accuracy was assessed using an infrared-camera-based tracking sensor and computed tomography images. The results showed that the suggested localization scheme can be effectively used in the 2D US image-guided needle procedures.