The real x-ray dataset has voxel-wise accuracy around 81.83%, 87.77%, and 89.59% for twoview, four-view, and six-view reconstructions, respectively. The fourth experiment, which incorporates irregular shaped spheres into a model trained for regular spheres has the lowest reconstruction accuracy with 2 views. However, the fourth experiment shows the greatest improvement in voxel-wise accuracy with increasing projection views. Similar to the voxel-wise accuracy, the trend for structural similarity (SSIM) increases with the number of projection views (Figure ) for the real XCT data (e.g. Experiment #1) and synthetic irregular spheres (e.g. Experiment #2). Tomo-NeRF shows a high fidelity in structural restoration. When the input data is real XCT data the two-view reconstruction has a low accuracy but the structural similarity (SSIM) still reaches as high as 0.9971. The highest value of structural similarity (SSIM) is 0.9984 for the six-view reconstruction of the artificial sample (e.g. synthetic data with irregular spheres). Another way to evaluate the resiliency of the reconstruction is to extract local microstructure properties (e.g. porosity)