In this study, we propose a deep learning based two-stage breast CT reconstruction in the image domain. Unlike most methods, we use two separate models to improve the Breast CT image quality. In the first stage, a deep learning-based denoiser was used to remove the noise. In the second stage, a deep learning based image enhancement model is used to improve the image quality. We evaluated the proposed method on the AAPM 2021 sparse view CT reconstruction challenge dataset.1 The experimental results demonstrate that the proposed method performs better than all comparison methods.