Fig 2. Dice score visualization.

The Dice score is used to gauge model performance, ranging from 0 to 1. 1 corresponds to a pixel perfect match between the deep learning model output (red, A and D) and ground truth annotation (green, B and D). The model output with the higher Dice score (A) had greater overlap (C) with the ground truth (B) than the output (D) that had lesser overlap (F), as it did not predict that main pulmonary artery that was annotated in (E).