Bi-Level 3D-Image Reconstruction from Two Orthogonal Projections with Periodicity and Sub

As the Computed Tomography (CT) requires normally hundreds of projections to reconstruct the image, patients are exposed to more X-ray energy, which may cause side effects such as cancer. Even when the variability of the particles in the object is very less, the Computed Tomography requires many projections for good quality reconstruction. Discrete Tomography makes use of less variability of the particles in an object to obtain good quality reconstruction. Though the reconstructed image and the original image have same projections, in general, they need not be the same. In addition to projections, if a priori information about the image is known, it is possible to obtain good quality reconstructed image. Here we give an efficient polynomial time algorithm to reconstruct a bi-level 3D-(1,1,1)-periodic image from its projection images along x and y directions , and a known sub image of the unknown image by reducing our reconstruction problem to integral max flow problem. Keywords—Discrete Tomography, Image Reconstruction, Projection, Computed Tomography, Integral Max Flow Problem.