Independent of overall bone density, 3D trabecular bone (TB) architecture has been shown to play an important role in
conferring strength to the skeleton. Advances in imaging technologies such as micro-computed tomography (CT) and
micro-magnetic resonance (MR) now permit in vivo imaging of the 3D trabecular network in the distal extremities.
However, various experimental factors preclude a straightforward analysis of the 3D trabecular structure on the basis of
these in vivo images. For MRI, these factors include blurring due to patient motion, partial volume effects, and
measurement noise. While a variety of techniques have been developed to deal with the problem of patient motion, the
second and third issues are inherent limitations of the modality. To address these issues, we have developed a series of
robust processing steps to be applied to a 3D MR image and leading to a 3D skeleton that accurately represents the
trabecular bone structure. Here we describe the algorithm, provide illustrations of its use with both specimen and in vivo
micro-MR images, and discuss the accuracy and quantify the relationship between the original bone structure and the
resulting 3D skeleton volume.