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Simultaneous dual isotope imaging (99mTc/123I) has potential clinical applications but has not been implemented in the clinic. The aim of this work was to design an artificial neural network (ANN) for crosstalk and scatter correction using a smaller number of energy windows (8) than we had previously proposed (26) to allow implementation on some clinical cameras, and to validate our approach using realistic Monte Carlo simulations and anthropomorphic brain phantom acquisitions. Monte Carlo simulations of dual isotope SPECT studies of a digital brain phantom and physical acquisitions of the striatal brain phantom were used to validate our approach. Corrected projections were reconstructed using an iterative ordered subsets expectation maximization (OSEM) algorithm that modeled nonuniform attenuation and variable collimator response in the projector/backprojector. Results: In Monte Carlo simulations, ANN26 and ANN8 yielded similarly accurate quantitation of 123I activity (bias <7%) in all brain structures. An asymmetric windowing method (AW) yielded accurate estimation in the striata (bias <7%) but not in other brain structures. The estimation bias of 99mTc primary activity was <10% in all brain structures with ANN26 and ANN8.