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Detecting a Needle in Carm X-ray Images

This paper presents an algorithm to detect a rigid straight biopsy needle in multi-view C-arm X-ray images and reconstruct its tip and orientation in 3D-space. Several well known computer vision techniques are applied to achieve this goal. The processing pipeline that we describe consists of five stages containing a denoising and preprocessing stage with Gaussian filtering, computing the Hessian tensorfield and a Radon transform for ridge detection, needle tip detection, the reconstruction of the data into 3Dspace with Direct Linear Transform and improving robustness by backprojection. The processing steps are described in detail, a short overview is given about the surrounding application and finally we present the evaluation results of the experiments on real X-ray imaging data.