PURPOSE: To present a 2-stage framework that robustly extracts and maps reliable lung ventilation surrogates based on subregional respiratory dynamics (SRDs) measured from 4-dimensional computed tomography (4DCT) images, with comprehensive consideration of spatial and temporal heterogeneity in the ventilation process over the respiratory cycle. METHODS AND MATERIALS: We retrospectively analyzed 3 subject cohorts from the Ventilation and Medical Pulmonary Image Registration Evaluation challenge containing 4DCT and reference ventilation imaging (RefVI) scans. Lung subregions were partitioned on the 4DCT end-of-exhale base phase using anatomically constrained simple linear iterative clustering, whereas sliding-preserved interphase image registrations were performed between the base and other phases. SRDs of breathing-induced volume and intensity changes were tracked across phases utilizing the displacement fields. Voxel-level representations integrating mechanical collapsibility and physiological tissue density (V RESULTS: The extracted SRD highlighted temporally varying subregional volume and computed tomography intensity changes related to underlying functional physiology and pathologies. For imaging performance, the median Spearman correlation coefficients between V CONCLUSIONS: V