Single particle cryo-electron microscopy studies, but also data from tomographic experiments, often result in volumetric 3D reconstructions of low- to intermediate resolution. Although a direct atomic interpretation is not feasible at these levels of detail, one may be able to extract structural information that describes the overall conformation of the molecular system. Especially a detection of secondary structure elements, would aid in a further description of large macromolecular complexes.On the other hand, the limited resolution often prohibits a clear visual identification of those elements.We therefore propose a novel algorithmic tool, which is able to annotate automatically volumetric reconstructions and determines the secondary structure elements inside the maps. Our technique is based on a multi-stage analysis: In a first step, a spatial digital path filtering technique is applied, which is able to enhance local features that may characterize helices or sheets.In a second step those features are extracted by combining the voxel information and modeling the likelihood of the presence of a secondary structure element at the specific location. To evaluate the performance of our algorithm, we have tested it using both, synthetic and experimental maps. The results show that our software is able to successfully annotate even intermediate-resolution maps. In addition, we have combined the before-mentioned algorithmic technique with our visualization system Sculptor. Sculptor provides a user-friendly environment, which enables not only an interactive pre-processing of the volume data, but also an intuitive exploration of the results.This work was supported by NIH grant R01GM62968, by a grant from the Gillson Longenbaugh Foundation, and by startup funds of the University of Texas Health Science Center at Houston.