We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.Index Terms-Brain tissue models, hidden Markov random fields models, magnetic resonance imaging, partial volume, statistical classification, validation study.

An imaging technique may be helpful in the identification of cerebral penumbra in acute stroke patients and thus in the selection of patients for thrombolytic therapy. Perfusion CT and DWI/PWI are equivalent in this task.

We propose a new exact Euclidean distance transformation (DT) by propagation, using bucket sorting. A fast but approximate DT is first computed using a coarse neighborhood. A sequence of larger neighborhoods is then used to gradually improve this approximation. Computations are kept short by restricting the use of these large neighborhoods to the tile borders in the Voronoi diagram of the image. We assess the computational cost of this new algorithm and show that it is both smaller and less image-dependent than all other DTs recently proposed. Contrary to all other propagation DTs, it appears to remain o(n 2 ) even in the worst-case scenario.

We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.

A sound that we hear in a natural setting allows us to identify the sound source and localize it in space. The two aspects can be disrupted independently as shown in a study of 15 patients with focal right-hemispheric lesions. Four patients were normal in sound recognition but severely impaired in sound localization, whereas three other patients had difficulties in recognizing sounds but localized them well. The lesions involved the inferior parietal and frontal cortices, and the superior temporal gyrus in patients with selective sound localization deficit; and the temporal pole and anterior part of the fusiform, inferior and middle temporal gyri in patients with selective recognition deficit. These results suggest separate cortical processing pathways for auditory recognition and localization.