ADART: An Adaptive Algebraic Reconstruction Algorithm for Discrete Tomography

• Published in: IEEE transactions on image processing Vol. 20; no. 8; pp. 2146 - 2152
• Main Authors: Maestre-Deusto, F. J., Scavello, G., Pizarro, J., Galindo, P. L.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.08.2011; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: ADART; Algebra; algebraic reconstruction technique; Algorithms; Applied sciences; Borders; DART; discrete tomography; Equations; Exact sciences and technology; Head - anatomy & histology; Humans; Image processing; Image Processing, Computer-Assisted - methods; Image reconstruction; Information, signal and communications theory; Linear systems; Models, Theoretical; Noise; Phantoms, Imaging; Pixel; Pixels; Reconstruction; Reconstruction algorithms; Reduction; Signal processing; Studies; Telecommunications and information theory; Tomography; Tomography - methods; Transforms; DART; Linear system; ADART; Image processing; Adaptive algorithm; discrete tomography; algebraic reconstruction technique; Error rate; Tomography; Iterative method; Background noise; Image reconstruction
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/TIP.2011.2114894

In this paper we suggest an algorithm based on the Discrete Algebraic Reconstruction Technique (DART) which is capable of computing high quality reconstructions from substantially fewer projections than required for conventional continuous tomography. Adaptive DART (ADART) goes a step further than DART on the reduction of the number of unknowns of the associated linear system achieving a significant reduction in the pixel error rate of reconstructed objects. The proposed methodology automatically adapts the border definition criterion at each iteration, resulting in a reduction of the number of pixels belonging to the border, and consequently of the number of unknowns in the general algebraic reconstruction linear system to be solved, being this reduction specially important at the final stage of the iterative process. Experimental results show that reconstruction errors are considerably reduced using ADART when compared to original DART, both in clean and noisy environments.