Replication Data for: Adapting super-resolution reconstruction for skeletal analysis of clinical computed tomography data

3D model files supporting the findings of "Adapting super-resolution reconstruction for skeletal analysis of clinical computed tomography data." This study evaluates the utility of an automated super-resolution reconstruction (SRR) framework in generating high-resolution skeletal models from multiple orthogonal thick-slice CT stacks. Archived CT scans of long bones from 33 individuals (aged 0 to 16 years) were retrospectively collected from the National Taiwan University Hospital. Two sets of models were generated per bone: one derived from the original low-resolution, thick-slice CT image stacks (“pre”), and one from the reconstructed high-resolution volumes produced using the NiftyMIC pipeline (“post”).