With advances in deep learning, feasibility has been investigated for MREPT reconstruction showing interesting results. However whether images denoised with deep learned reconstruction will improve EPT map quality has not been investigated. After denoising of complex data acquired with a DL algorithm, EPT maps were generated with phase based 2D-weighted polynomial fitting. Use of DL, shows better results as compared to conventionally generated maps (i.e. decreased NRMSE, increased PSNR and SSIM, with increasing denoising levels), and results in sharper appearing maps. Spreading of boundary artifacts are not observed with increasing denoising factors.