Andrea Rueda

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Resolution in Magnetic Resonance (MR) is limited by diverse physical, technological and economical considerations. In conventional medical practice, resolution enhancement is usually performed with bicubic or B-spline interpolations, strongly affecting the accuracy of subsequent processing steps such as segmentation or registration. This paper presents a(More)
In magnetic resonance imaging (MRI), accuracy and precision with which brain structures may be quantified are frequently affected by the partial volume (PV) effect. PV is due to the limited spatial resolution of MRI compared to the size of anatomical structures. Accurate classification of mixed voxels and correct estimation of the proportion of each pure(More)
Magnetic resonance (MR) provides a non-invasive way to investigate changes in the brain resulting from aging or neurodegenerative disorders such as Alzheimer's disease (AD). Performing accurate analysis for population studies is challenging because of the interindividual anatomical variability. A large set of tools is found to perform studies of brain(More)
Deformable registration of cortical surfaces facilitates longitudinal and intergroup comparisons of cortical structure and function in the study of many neurodegenerative diseases. Non-rigid cortical matching is a challenging task due to the large variability between individuals and the complexity of the cortex. We present a new framework for computing(More)
In magnetic resonance imaging (MRI), accuracy of brain structures quantification may be affected by the partial volume (PV) effect. PV is due to the limited spatial resolution of MRI compared to the size of anatomical structures. When considering the cortex, measurements can be even more difficult as it spans only a few vox-els. In tight sulci areas, where(More)
Neurodegenerative diseases comprise a wide variety of mental symptoms whose evolution is not directly related to the visual analysis made by radiologists, who can hardly quantify systematic differences. Moreover, automatic brain morphometric analyses, that do perform this quantification, contribute very little to the comprehension of the disease, i.e., many(More)
—This paper presents a semi-automatic segmentation method to extract the liver volume from CT scans, based on discrete deformable surfaces with both a priori shape and intensity information. A shape model of the liver, represented as a triangular mesh, is built and is manually located in the region of interest, to be iteratively deformed in function of the(More)
High-quality cardiac magnetic resonance (CMR) images can be hardly obtained when intrinsic noise sources are present, namely heart and breathing movements. Yet heart images may be acquired in real time, the image quality is really limited and most sequences use ECG gating to capture images at each stage of the cardiac cycle during several heart beats. This(More)
In this paper we present a new deformation method which permits to generate smoothed representations of neuroanatomical structures. These surfaces are approximated by triangulated meshes which are evolved using an external velocity field, modified by a local curvature dependent contribution. This motion conserves local metric properties since the external(More)