Automatic needle localization in 3D ultrasound images for brachytherapy

Needle segmentation in ultrasound images may be the indispensable step to solve other problems, such as the detection of radioactive seeds in ultrasound images for brachytherapy treatment. In this paper we propose a novel method to localize accurately curved paths of flexible needles in three-dimensional (3D) ultrasound images. Our method is based on an automatic thresholding step where the bayesian classifier theory is applied to select a needle's voxels from the background. The next step consists in detecting the needle and representing its curvature. Here we propose to fit a parametric polynomial of low degree to representing the parabolic curvature. We describe a first evaluation on a data set of 9 patients.