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Lymph nodes have high clinical relevance because they are often affected by cancer, and also play an important role in all kinds of infections and inflammations in general. Lymph nodes are commonly examined using computed tomography (CT). Manually counting and measuring lymph nodes in CT volumes images is not only cumbersome but also introduces the problem of inter-observer variability and even intra-observer variability. Automatic detection is however challenging as lymph nodes are hard to see due to low contrast, irregular shape, and clutter. In this work, a top-down approach for lymph node detection in 3-D CT volume images is proposed. The focus is put on lymph nodes that lie in the region of the mediastinum. CT volumes that show the mediastinum are typically scans of the thorax or even the whole thoracic and abdominal region. Therefore, the first step of the method proposed in this work is to determine the visible portion of the body from a CT volume. This allows pruning the search space for mediastinal lymph nodes and also other structures of interest. Furthermore, it can tell whether the mediastinum is actually visible. The visible body region of an unknown test volume is determined by 1-D registration along the longitudinal axis with a number of reference volumes whose body regions are known. A similarity measure for axial CT slices is proposed that has its origin in scene classification. An axial slice is described by a spatial pyramid of histograms of visual words, which are code words of a quantized feature space. The similarity of two slices is measured by comparing their histograms. As features, descriptors of the Speeded Up Robust Features are used. This work proposes an extension of the SURF descriptors to an arbitrary number of dimensions (N-SURF). Here, we make use of 2-SURF and 3-SURF descriptors. The mediastinal body region contains a number of structures that can be confused with lymph nodes. One of them is the esophagus. Its attenuation coefficient is usually similar, and at the same time it ...