A Local and Iterative Neural Reconstruction Algorithm for Cone-Beam Data

نویسنده

  • Ignazio Gallo
چکیده

This work presents a new neural algorithm designed for the reconstruction of tomographic images from Cone Beam data. The algorithm is iterative and based on a set of neural networks that are working locally and sequentially. The algorithm was compared with the iterative ART algorithm and the filtered backprojection (FBP) method. The results show how the proposed algorithm is much more accurate even in the presence of noise and under conditions of lack of data.

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تاریخ انتشار 2009