01209nam a2200205 a 450000100080000000500110000800800410001910000210006024501180008126001300019952005190032965000150084865000150086365000150087865300170089365300100091065300310092065300280095170000240097910074502020-01-17       2003    bl uuuu     u00u1 u    #d1 aDE PIERRO, A. R.  aFast scaled gradient decomposition methods for maximum likelihood transmission tomography.h[electronic resource]  aIn: ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE EMBS, 25., 2003, Cancun. Proceedings... [S.l.: s.n.], 2003. p. 829-832.c2003  aNew iterative algorithms are presented for Maximum Likelihood (ML) and Regularized Maximum Likelihood (MAP) reconstruction in Transmission Tomography (CT). The algorithms are natural extensions to CT of RAMLA, a well known method for ML reconstruction in Emission Computed Tomography (ECT). We show that the new algorithm for ML solutions produces similar, or even better results than EM-like algorithms, but in much fewer iterations. Also, its convergence properties are better than other ordered subsets methods.  aAlgorithms  aTomography  aTomografia  aAlgoritmo EM  aRAMLA  aTransmissão de tomografia  aTransmission tomography1 aYAMAGISHI, M. E. B.