Verónica Médina-Bañuelos

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Brain magnetic resonance imaging segmentation is accomplished in this work by applying nonparametric density estimation, using the mean shift algorithm in the joint spatial-range domain. The quality of the class boundaries is improved by including an edge confidence map, that represents the confidence of truly being in the presence of a border between(More)
PURPOSE This study examines the effect of static and dynamic leg exercises on heart rate variability (HRV) and blood pressure variability (BPV) in humans. METHODS 10 healthy male subjects were studied at rest, during static exercise performed at 30% of maximal voluntary contraction (SX30), and during dynamic cycling exercises done at 30% of VO2max (DX30)(More)
Magnetic Resonance Imaging (MRI) is increasingly used for the diagnosis and monitoring of neurological disorders. In particular Diffusion-Weighted MRI (DWI) is highly sensitive in detecting early cerebral ischemic changes in acute stroke. Cerebral infarction lesion segmentation from DWI is accomplished in this work by applying nonparametric density(More)
Previous work has shown that the segmentation of anatomical structures on 3D ultrasound data sets provides an important tool for the assessment of the fetal health. In this work, we present an algorithm based on a 3D statistical shape model to segment the fetal cerebellum on 3D ultrasound volumes. This model is adjusted using an ad hoc objective function(More)
Magnetic resonance (MR) has been accepted as the reference image study in the clinical environment. The development of new sequences has allowed obtaining diverse images with high clinical importance and whose interpretation requires their joint analysis (multispectral MRI). Recent approaches to segment MRI point toward the definition of hybrid models,(More)
To delineate arbitrarily shaped clusters in a complex multimodal feature space, such as the brain MRI intensity space, often requires kernel estimation techniques with locally adaptive bandwidths, such as the adaptive mean shift procedure. Proper selection of the kernel bandwidth is a critical step for a better quality in the clustering. This paper presents(More)
Robust high-breakdown-point location estimators are employed to analyze image stacks under the piecewise constant image structure model. To reduce the effect of bias along the Z-axis, the class parameters are extracted using three consecutive slices, The segmentation algorithm first determines the most reliable seed regions, which are then used in a(More)