Anatomical structure characterization of fetal ultrasound images using texture-based segmentation technique via an interactive MATLAB application.

Objective: To describe the texture characteristics in several anatomical structures within fetal ultrasound images by applying an image segmentation technique through an application developed in MATLAB mathematical processing software.

Methods: Prospective descriptive observational study with an analytical component. 2D fetal ultrasound images were acquired in patients admitted to the Maternal Fetal Medicine Unit of the Hospital de San José, Bogotá-Colombia.

Kernel temporal enhancement approach for LORETA source reconstruction using EEG data.

Reconstruction of brain sources from magnetoencephalography and electroencephalography (M/EEG) data is a well known problem in the neuroengineering field. A inverse problem should be solved and several methods have been proposed. Low Resolution Electromagnetic Tomography (LORETA) and the different variations proposed as standardized LORETA (sLORETA) and the standardized weighted LORETA (swLORETA) have solved the inverse problem following a non-parametric approach, that is by setting dipoles in the whole brain domain in order to estimate the dipole positions from the M/EEG data and assuming some spatial priors.

Multiple-output support vector machine regression with feature selection for arousal/valence space emotion assessment.

Human emotion recognition (HER) allows the assessment of an affective state of a subject. Until recently, such emotional states were described in terms of discrete emotions, like happiness or contempt. In order to cover a high range of emotions, researchers in the field have introduced different dimensional spaces for emotion description that allow the characterization of affective states in terms of several variables or dimensions that measure distinct aspects of the emotion.