Abstract
Localization of a needle’s tip in ultrasound images is often a challenge during percutaneous procedures due to the inherent limitations of ultrasound imaging. A new method is proposed for tip localization with curvilinear arrays using local image statistics over a region extended from the partially visible needle shaft. First, local phase-based image projections are extracted using orientation-tuned Log-Gabor filters to coarsely estimate the needle trajectory. The trajectory estimation is then improved using a best fit iterative method. To account for the typically discontinuous needle shaft appearance, a geometric optimization is then performed that connects the extracted inliers of the point cloud. In the final stage, the enhanced needle trajectory points are passed to a feature extraction method that uses a combination of spatially distributed image statistics to enhance the needle tip. The needle tip is localized using the enhanced images and calculated trajectory. Validation results obtained from 150 ex vivo ultrasound scans show an accuracy of 0.43 ±0.31 mm for needle tip localization.
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Hacihaliloglu, I., Beigi, P., Ng, G., Rohling, R.N., Salcudean, S., Abolmaesumi, P. (2015). Projection-Based Phase Features for Localization of a Needle Tip in 2D Curvilinear Ultrasound. In: Navab, N., Hornegger, J., Wells, W., Frangi, A. (eds) Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015. MICCAI 2015. Lecture Notes in Computer Science(), vol 9349. Springer, Cham. https://doi.org/10.1007/978-3-319-24553-9_43
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