Comparison Of 3-D Tomographic Algorithms For Vascular Reconstruction

We make a comparison of the performances of various three-dimensional reconstruction algorithms for situations where only few conic projections of a vascular tree are available. This problem is ill-posed and prior information must therefore be used to regularize the solution. We restrict ourselves to methods that are able to handle the sparseness and the non-negativity that caracterize a iodinated vascular structure: the Extreme Value Technique and related methods, and the Algebraic Reconstruction Technique. The results we obtained led us to derive a new method based on a two steps detection-estimation scheme.