Turbo spin echo (TSE) imaging with variable flip angle (VFA) is commonly used for three-dimensional (3D) high resolution intracranial vessel wall imaging. However, different tissues may experience various blurring effects particularly for longer TSE factor. In this study, a deep convolutional neural network is trained to provide a solution for this special deblurring problem. Combined with a signal-to-noise ratio (SNR)-priority VFA design scheme, the developed technique can provide a better tradeoff across scan efficiency, point spread function and SNR for 3D TSE acquisitions. Preliminary results have demonstrated its improvement for sharper delineation of intracranial vessel wall and plaque boundaries at isotropic 0.5mm resolution.