Visualization, reconstruction, and integration of neuronal structures in digital brain atlases.

Brain atlases are used in neuroanatomy to define the spatial layout of neuronal structures. Their digital variant can serve as a database and common reference frame for integrating data from different biological experiments. This article presents an overview of methods for three-dimensional visualization of neuroanatomical image data, reconstructing neuronal structures from image data, creating digital brain atlases, and registering data in an atlas. This enables analysis of spatial relations between individual structures imaged in different experiments as well as between these structures and the atlas.

Registration of different phases of contrast-enhanced CT/MRI data for computer-assisted liver surgery planning: evaluation of state-of-the-art methods.

The exact localization of intrahepatic vessels in relation to a tumour is an important issue in oncological liver surgery. For computer-assisted preoperative planning of surgical procedures high quality vessel models are required. In this work we show how to generate such models on the basis of registered CT or MRI data at different phases of contrast agent propagation. We combine well-established intensity-based rigid and non-rigid registration approaches using Mutual Information as distance measure with different masking strategies as well as intensity inhomogeneity correction for MRI data. Non-rigid deformations are modelled by multilevel cubic B-splines. Quantitative evaluations of 5 MRI and 5 CT image pairs show that the liver moves rigidly 7.2 (+/- 4.2) mm on average, while the remaining non-rigid deformations range from 1.4-3 mm. As a result we find that masked rigid registration is necessary and in many cases also sufficient on clinical data. After non-rigid registration the matching shows no deviations in most cases.