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Although numerous methods to register brains of different individuals have been proposed, no work has been done, as far as we know, to evaluate and objectively compare the performances of different nonrigid (or elastic) registration methods on the same database of subjects. In this paper, we propose an evaluation framework, based on global and local measures of the relevance of the registration. We have chosen to focus more particularly on the matching of cortical areas, since intersubject registration methods are dedicated to anatomical and functional normalization, and also because other groups [7] have shown the relevance of such registration methods for deep brain structures. Experiments were conducted using 6 methods on a database of 18 subjects. The global measures used show that the quality of the registration is directly related to the transformation's degrees of freedom. More surprisingly, local measures based on the matching of cortical suici did not show significant differences between rigid and non rigid methods. Index Terms--Atlas matching, cortical suici, evaluation, MRI, neuroanatomy, nonrigid registration.

Respiratory motion can blur the tomographic reconstruction of positron emission tomography or single-photon emission computed tomography (SPECT) images, which subsequently impair quantitative measurements, e.g. in the upper abdomen area. Respiratory signal phase-based gated reconstruction addresses this problem, but deteriorates the signal-to-noise ratio (SNR) and other intensity-based quality measures. This paper proposes a 3D reconstruction method dedicated to micro-SPECT imaging of mice. From a 4D acquisition, the phase images exhibiting motion are identified and the associated list-mode data are discarded, which enables the reconstruction of a 3D image without respiratory artefacts. The proposed method allows a motion free reconstruction exhibiting both satisfactory count statistics and accuracy of measures. With respect to standard 3D reconstruction (non-gated 3D reconstruction) without breathing motion correction, an increase of 14.6% of the mean standardized uptake value has been observed, while, with respect to a gated 4D reconstruction, up to 60% less noise and an increase of up to 124% of the SNR have been demonstrated. [ABSTRACT FROM AUTHOR]

Medical images are of great importance in radiotherapy, which became a privileged application field for image processing techniques. Moreover, because of the progression of the computers’ performances, these techniques are also in full expansion. Today, the recent developments of the radiotherapy (3DCR, IMRT) offer a huge place to them. Effectively, they can potentially answer to the precision requirements of the modern radiotherapy, and may then contribute to improve the delivered treatments. The purpose of this article is to present the different image processing techniques that are currently used in radiotherapy (including image matching and segmentation) as they are described in the literature. [Copyright &y& Elsevier]

This paper presents a 4D (3D+time) echocardiographic image anisotropic filtering and a 3D model-based segmentation system. To improve the extraction of left ventricle boundaries, we rely on two preprocessing stages. First, we apply an anisotropic filter that reduces image noise. This 4D filter takes into account the spatial and temporal nature of echocardiographic images. Second, we adapt the usual gradient filter estimation to the cylindrical geometry of the 3D ultrasound images. The reconstruction of the endocardium takes place by deforming a deformable simplex mesh having an a priori knowledge of left ventricle shape and that is guided by a region-based data attraction force. The external force formulation improves the segmentation robustness against noise and outliers. We illustrate our method by showing experimental results on very challenging sparse and noisy ultrasound images of the heart and by computing quantitative measurements of the left ventricle volume. [Copyright &y& Elsevier]