Simultaneous synthesis of perfusion and ventilation images from CT using a dual‐decoder residual attention network for lung disease diagnosis

We have developed a dual-decoder residual attention network that enables the simultaneous synthesis of lung perfusion and ventilation images from three-dimensional CT. Preliminary results indicate moderate-to-high structural-wise and functional-wise concordances, and our proposed model demonstrates comparable accuracy when benchmarked against single-decoder models. The synthesized perfusion and ventilation images can potentially be used for precise diagnosis and guiding functional lung avoidance radiotherapy.