Abstract. We present a hierarchical object{based deformable atlas, a promising new approach for the automatic localization and quantitative analysis of neuroanatomy in MR images. The 3D nite element-based elastic atlas combines the advantages of both volumetric { and surface{ based deformable

not often offer enough contrast to robustly obtain a good detection of all internal brain structures, not least the deep gray matter nuclei. We propose digital atlases that deform to fit the image data to be analyzed. In this application, deformable atlases are employed for the detection and segmentation

model points are attracted to the brain surface. A conjugate gradient method minimizes the energy function, allowing the model to automatically converge to the smoothed brain surface. Finally, labels are propagated from the deformed atlas onto the high-resolution brain surface. Index Terms—Brain atlas

offer enough contrast to robustly obtain a good detection of all internal brain structures, not least the deep grey matter nuclei. We propose a method that incorporates prior anatomical knowledge in the shape of digital atlases that deform to fit the image data to be analysed. Our technique is based

Compensating for intraoperative brain shift using computational models has shown promising results. Since computational time is an important factor during neurosurgery, a priori knowledge of the possible sources of deformation can increase the accuracy of model-updated image-guided systems (MUIGS

views with simulated projections of a statistical anatomical model, which is deformably registered to match the data in the C-arm images. This paper presents the methods used to create the atlas and to register it with x-ray images. We compare the results of seven leave-one-out simulated hybrid

Abstract not found

structures (e.g. hippocampi), which are not easily identified on axial imaging. In this pilot study, a commercially available digital atlas was used to identify cryptic neural structures (hippocampus, optic radiations, and visual cortices) in 6 patients who received intensity modulated radiation therapy

Striking variations in brain structure, especially in the gyral patterns of the human cortex, present fundamental challenges in human brain mapping. Probabilistic brain atlases, which encode information on structural and functional variability in large human populations, are powerful research tools

To evaluate our system for elastically deforming a three-dimensional atlas to match anatomical brain images, six deformed versions of an atlas were generated. The deformed atlases were created by elastically mapping an anatomical brain atlas onto different MRI brain image volumes. The mapping