Automatic segmentation of myocardial 3D whole-heart T1 and T2 maps using a nnU-Net.

The high amount of data obtained from a single 3D whole heart multiparametric scan (up to ~40 slices per parametric map) increases considerably the time required to segment and analyse the quantitative maps. Thus, an automated segmentation tool for these maps is desirable to perform this otherwise prohibitively laborious task. In this work, we leverage the potential of nnU-Net to perform fast, automated segmentation of 3D whole-heart simultaneous T1 and T2 maps and show its feasibility to predict segmentation masks with comparable quality while shortening the segmentation and analysis time by ~100x.