PT Journal AU NEXT Collaboration (Simon, Aea Gomez-Cadenas, JJ Alvarez, V Benlloch-Rodriguez, JM Botas, A Carcel, S Carrion, JV Diaz, J Felkai, R Ferrario, P Laing, A Liubarsky, I Lopez-March, N Martin-Albo, J Martinez, A Muñoz Vidal, J Musti, M Nebot-Guinot, M Novella, P Palmeiro, B Perez, J Querol, M Renner, J Rodriguez, J Sorel, M Torrent, J Yahlali, N TI Application and performance of an ML-EM algorithm in NEXT SO Journal of Instrumentation JI J. Instrum. PY 2017 BP P08009 - 22pp VL 12 DI 10.1088/1748-0221/12/08/P08009 LA English DE Gaseous imaging and tracking detectors; Image reconstruction in medical imaging; Time projection Chambers (TPC); Medical-image reconstruction methods and algorithms; computer-aided software AB The goal of the NEXT experiment is the observation of neutrinoless double beta decay in Xe-136 using a gaseous xenon TPC with electroluminescent amplification and specialized photodetector arrays for calorimetry and tracking. The NEXT Collaboration is exploring a number of reconstruction algorithms to exploit the full potential of the detector. This paper describes one of them: the Maximum Likelihood Expectation Maximization (ML-EM) method, a generic iterative algorithm to find maximum-likelihood estimates of parameters that has been applied to solve many different types of complex inverse problems. In particular, we discuss a bi-dimensional version of the method in which the photosensor signals integrated over time are used to reconstruct a transverse projection of the event. First results show that, when applied to detector simulation data, the algorithm achieves nearly optimal energy resolution (better than 0.5% FWHM at the Q value of 136Xe) for events distributed over the full active volume of the TPC. ER