A deep learning reconstruction was evaluated for use in T2w breast MRI. Breast radiologists scored deep learning (DL) images significantly higher than non-DL images in four categories: artifacts, perceived signal-to-noise ratio, sharpness, and overall quality. DL was then used to improve the quality of high-resolution T2w breast series acquired in clinically-acceptable scan times. High resolution protocols typically require compromise between scan time and image quality. However, implementation of a deep learning reconstruction allowed for shorter scan times while maintaining diagnostic image quality. A deep learning reconstruction could allow for a clinically-feasible, high-resolution T2w acquisition.