Principles of computerized tomographic imaging
Principles of computerized tomographic imaging
On Stability, Error Correction, and Noise Compensation in Discrete Tomography
SIAM Journal on Discrete Mathematics
Stability results for the reconstruction of binary pictures from two projections
Image and Vision Computing
A Network Flow Algorithm for Reconstructing Binary Images from Continuous X-rays
Journal of Mathematical Imaging and Vision
Fundamentals of Computerized Tomography: Image Reconstruction from Projections
Fundamentals of Computerized Tomography: Image Reconstruction from Projections
Discrete tomography by convex-concave regularization and D.C. programming
Discrete Applied Mathematics - Special issue: IWCIA 2003 - Ninth international workshop on combinatorial image analysis
An Algebraic Framework for Discrete Tomography: Revealing the Structure of Dependencies
SIAM Journal on Discrete Mathematics
Bounds on the difference between reconstructions in binary tomography
DGCI'11 Proceedings of the 16th IAPR international conference on Discrete geometry for computer imagery
DART: A Practical Reconstruction Algorithm for Discrete Tomography
IEEE Transactions on Image Processing
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Binary tomography deals with the problem of reconstructing a binary image from its projections. Depending on properties of the unkown original image, the constraint that the image is binary enables accurate reconstructions from a relatively small number of projection angles. Even in cases when insufficient information is available to compute an accurate reconstruction of the complete image, it may still be possible to determine certain features of it, such as straight boundaries, or homogeneous regions. In this paper, we present a computational technique for discovering the possible presence of such features in the unknown original image. We present numerical experiments, showing that it is often possible to accurately identify the presence of certain features, even without a full reconstruction.