Selective ensemble methods for deep learning segmentation of major vessels in invasive coronary angiography.

Proposed methods successfully reduced morphological errors in the predicted masks and were able to enhance the robustness of the automatic segmentation. The results suggest better applicability of real-time QCA-based diagnostic methods in routine clinical settings.