Magnetic Resonance parametric mapping can provide quantitative information to characterize tissue properties. Recently, a single-shot T2 mapping method based on Multiple Overlapping-Echo Detachment (MOLED) planar imaging was proposed. However, limited echo time ranges still affected the reconstruction accuracy of the T2 values, especially when large T2 value ranges were present. In this abstract, MOLED was expanded through multiple-echo-train acquisitions that achieved high accuracy and better texture. The deep convolution neural network was used to reconstruct T2 maps, B1 maps and spin densities in synchrony. The sequence efficiencies were demonstrated in digital-brain, phantom and human-brain experiments.