Purpose: We present a phase-contrast x-ray tomography study of wild type C57BL/6 mouse hearts as a nondestructive approach to the microanatomy on the scale of the entire excised organ. Based on the partial coherence at a home-built phase-contrast μ-CT setup installed at a liquid metal jet source, we exploit phase retrieval and hence achieve superior image quality for heart tissue, almost comparable to previous synchrotron data on the whole organ scale. Approach: In our work, different embedding methods and heavy metal-based stains have been explored. From the tomographic reconstructions, quantitative structural parameters describing the three-dimensional (3-D) architecture have been derived by two different fiber tracking algorithms. The first algorithm is based on the local gradient of the reconstructed electron density. By performing a principal component analysis on the local structure-tensor of small subvolumes, the dominant direction inside the volume can be determined. In addition to this approach, which is already well established for heart tissue, we have implemented and tested an algorithm that is based on a local 3-D Fourier transform. Results: We showed that the choice of sample preparation influences the 3-D structure of the tissue, not only in terms of contrast but also with respect to the structural preservation. A heart prepared with the evaporation-of-solvent method was used to compare both algorithms. The results of structural orientation were very similar for both approaches. In addition to the determination of the fiber orientation, the degree of filament alignment and local thickness of single muscle fiber bundles were obtained using the Fourier-based approach. Conclusions: Phase-contrast x-ray tomography allows for investigating the structure of heart tissue with an isotropic resolution below 10 μm. The fact that this is possible with compact laboratory instrumentation opens up new opportunities for screening samples and optimizing sample preparation, also prior to synchrotron beamtimes. Further, results from the structural analysis can help in understanding cardiovascular diseases or can be used to improve computational models of the heart.