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Biomedical subjects

G Sapiro

Publications and source records attributed to G Sapiro.

9 recordsLinked to original sources
PubMed2001

A system for the generation of curves on 3D brain images.

In this study, a computational optimal system for the generation of curves on triangulated surfaces representing 3D brains is described. The algorithm is based on optimally computing geodesics on the triangulated surfaces following Kimmel and Sethian ([1998]: Proc Natl Acad Sci 95:15). The system can be used to compute geodesic curves for accurate distance measurements as well as to detect sulci and gyri. These curves are defined based on local surface curvatures that are computed following a novel approach presented in this study. The corresponding software is available to the research community.

Algorithms↗
PubMed2001

Anisotropic 2-D and 3-D averaging of fMRI signals.

A novel method for denoising functional magnetic resonance imaging temporal signals is presented in this note. The method is based on progressively enhancing the temporal signal by means of adaptive anisotropic spatial averaging. This average is based on a new metric for comparing temporal signals corresponding to active fMRI regions. Examples are presented both for simulated and real two and three-dimensional data. The software implementing the proposed technique is publicly available for the research community.

Algorithms↗
PubMed2000

Segmenting skin lesions with partial-differential-equations-based image processing algorithms.

In this paper, a partial-differential equations (PDE)-based system for detecting the boundary of skin lesions in digital clinical skin images is presented. The image is first preprocessed via contrast-enhancement and anisotropic diffusion. If the lesion is covered by hairs, a PDE-based continuous morphological filter that removes them is used as an additional preprocessing step. Following these steps, the skin lesion is segmented either by the geodesic active contours model or the geodesic edge tracing approach. These techniques are based on computing, again via PDEs, a geodesic curve in a space defined by the image content. Examples showing the performance of the algorithm are given.

Algorithms↗
PubMed1999

Region tracking on level-sets methods.

Since the work by Osher and Sethian on level-sets algorithms for numerical shape evolutions, this technique has been used for a large number of applications in numerous fields. In medical imaging, this numerical technique has been successfully used, for example, in segmentation and cortex unfolding algorithms. The migration from a Lagrangian implementation to a Eulerian one via implicit representations or level-sets brought some of the main advantages of the technique, i.e., topology independence and stability. This migration means also that the evolution is parametrization free. Therefore, we do not know exactly how each part of the shape is deforming and the point-wise correspondence is lost. In this note we present a technique to numerically track regions on surfaces that are being deformed using the level-sets method. The basic idea is to represent the region of interest as the intersection of two implicit surfaces and then track its deformation from the deformation of these surfaces. This technique then solves one of the main shortcomings of the very useful level-sets approach. Applications include lesion localization in medical images, region tracking in functional MRI (fMRI) visualization, and geometric surface mapping.

Algorithms↗
PubMed1997

Constant affine velocity predicts the 1/3 power law of planar motion perception and generation.

Numerous studies have shown that the power of 1/3 is important in relating Euclidean velocity to radius of curvature (R) in the generation and perception of planar movement. Although the relation between velocity and curvature is clear and very intuitive, no valid explanation for the specific 1/3 value has yet been found. We show that if instead of computing the Euclidean velocity we compute the affine one, a velocity which is invariant to affine transformations, then we obtain that the unique function of R which will give (constant) affine invariant velocity is precisely R1/3. This means that the 1/3 power law, experimentally found in the studies of hand-drawing and planar motion perception, implies motion at constant affine velocity. Since drawing/perceiving at constant affine velocity implies that curves of equal affine length will be drawn in equal time, we performed an experiment to further support this result. Results showed agreement between the 1/3 power law and drawing at constant affine velocity. Possible reasons for the appearance of affine transformations in the generation and perception of planar movement are discussed.

Analysis of Variance↗
PubMed1997

A subspace reverse-correlation technique for the study of visual neurons.

A new discrete-time reverse-correlation scheme for the study of visual neurons is proposed. The visual stimulus is generated by drawing with uniform probability, at each refresh time, an image from a finite set S of orthonormal images. We show that if the neuron can be modeled as a spatiotemporal linear filter followed by a static nonlinearity, the cross-correlation between the input image sequence and the cell's spike train output gives the projection of the receptive field onto the subspace spanned by S. The technique has been applied to the analysis of simple cells in the primary visual cortex of cats and macaque monkeys. Experimental results are presented where S spans a subspace of spatially low-pass signals. Advantages of the proposed scheme over standard white-noise techniques include improved signal to noise ratios, increased spatial resolution, and the possibility to restrict the study to particular subspaces of interest.

Animals↗
PubMed1997

Creating connected representations of cortical gray matter for functional MRI visualization.

We describe a system that is being used to segment gray matter from magnetic resonance imaging (MRI) and to create connected cortical representations for functional MRI visualization (fMRI). The method exploits knowledge of the anatomy of the cortex and incorporates structural constraints into the segmentation. First, the white matter and cerebral spinal fluid (CSF) regions in the MR volume are segmented using a novel techniques of posterior anisotropic diffusion. Then, the user selects the cortical white matter component of interest, and its structure is verified by checking for cavities and handles. After this, a connected representation of the gray matter is created by a constrained growing-out from the white matter boundary. Because the connectivity is computed, the segmentation can be used as input to several methods of visualizing the spatial pattern of cortical activity within gray matter. In our case, the connected representation of gray matter is used to create a flattened representation of the cortex. Then, fMRI measurements are overlaid on the flattened representation, yielding a representation of the volumetric data within a single image. The software is freely available to the research community.

Cerebral Cortex↗