3-D Reconstruction Of High Contrast Objects From Limited Conic X-Ray Projections

We address the problem of reconstructing a 3-D object using a few of its conic projections measured with a 2-D X-ray detector. This problem is ill-posed and prior information must therefore be used to regularize the solution. We propose a non-parametric method based on a detection-estimation scheme that is particulary well-suited to the reconstruction of sparse objects such as 3-D vascular structures. We present results of 3-D reconstruction obtained from both computer simulated and experimentally measured projections.

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