Hyperconnected Openings Codified in a Max Tree Structure: An Application for Skull-Stripping in Brain MRI T1.

This article presents two procedures involving a maximal hyperconnected function and a hyperconnected lower leveling to segment the brain in a magnetic resonance imaging T1 weighted using new openings on a max-tree structure. The openings are hyperconnected and are viscous transformations. The first procedure considers finding the higher hyperconnected maximum by using an increasing criterion that plays a central role during segmentation. The second procedure utilizes hyperconnected lower leveling, which acts as a marker, controlling the reconstruction process into the mask. As a result, the proposal allows an efficient segmentation of the brain to be obtained. In total, 38 magnetic resonance T1-weighted images obtained from the Internet Brain Segmentation Repository are segmented. The Jaccard and Dice indices are computed, compared, and validated with the efficiency of the Brain Extraction Tool software and other algorithms provided in the literature.

Digital Pregnancy Test Powered by an Air-Breathing Paper-Based Microfluidic Fuel Cell Stack Using Human Urine as Fuel.

The direct integration of paper-based microfluidic fuel cells (µFC's) toward creating autonomous lateral flow assays has attracted attention. Here, we show that an air-breathing paper-based µFC could be used as a power supply in pregnancy tests by oxidizing the human urine used for the diagnosis. We present an air-breathing paper-based µFC connected to a pregnancy test, and for the first time, as far as we know, it is powered by human urine without needing any external electrolyte. It uses TiO2-Ni as anode and Pt/C as cathode; the performance shows a maximum value of voltage and current and power densities of ∼0.96 V, 1.00 mA cm-2, and 0.23 mW cm-2, respectively. Furthermore, we present a simple design of a paper-based µFC's stack powered with urine that shows a maximum voltage and maximum current and power densities of ∼1.89 V, 2.77 mA cm-2 and 1.38 mW cm-2, respectively, which powers the display of a pregnancy test allowing to see the analysis results.

A Deep Learning Approach for Predicting Multiple Sclerosis.

This paper proposes a deep learning model based on an artificial neural network with a single hidden layer for predicting the diagnosis of multiple sclerosis. The hidden layer includes a regularization term that prevents overfitting and reduces the model complexity. The purposed learning model achieved higher prediction accuracy and lower loss than four conventional machine learning techniques. A dimensionality reduction method was used to select the most relevant features from 74 gene expression profiles for training the learning models. The analysis of variance test was performed to identify the statistical difference between the mean of the proposed model and the compared classifiers. The experimental results show the effectiveness of the proposed artificial neural network.

Differences in the Visual Performances of Patients with Strabismus, Amblyopia, and Healthy Controls.

The aim of this paper is to use the new definition of amblyopia and to define the overall visual performance of healthy controls (HCs), patients with strabismus (PS), and patients with refractive amblyopia (PRA), based on the interaction of selected visual abilities. METHOD: A total of 398 participants were divided in three groups: HCs, PRA, and PS. Variables such as visual acuity, refractive state, degree of stereopsis, phoria state, magnitude, and type of deviation were analyzed using parametric and non-parametric tests. RESULTS: Binocular visual acuity at near is the unique predictor factor for stereopsis in PRA and PS, while age relates to the amount of binocular visual acuity at near, only for PS with stereopsis. Binocular visual acuity at near and phoria states relate to each other in PRA. Binocular visual acuity at near and far in PS is better than PRA, with no differences in the degree of stereopsis. Stereoblind patients were only found among PS (36%). Only (44.9%) of PS had amblyopia. Exophoria predominated among PRA (69.72%) and HCs (78.87%), while exotropia was the predominant deviation in PS (60.54%). Hyperopia was the predominate refractive error among the groups, HCs (74.65%), PRA (79.82%), and PS (59.85%), followed by astigmatism. INTERPRETATION: HCs perform better than PS and PRA. The visual performance of PS with stereopsis and PRA is similar. Binocular visual acuity at near can predict the degree of stereopsis, and stereoblind patients are exclusively related to strabismus.

Distortion Calculation Method Based on Image Processing for Automobile Lateral Mirrors.

The automobile lateral-view mirrors are the most important visual support for driver safety; therefore, it is important they have robust quality control. Typically, the distortion of a lateral-view mirror is measured using the JIS-D-5705 standard; however, this methodology requires an expert person to perform the measurements and calculations manually, which can induce measurement errors. In this work, a semi-automatic distortion calculation method based on image processing is presented. Distortion calculations of five commercial mirrors from different manufacturers were performed, and a comparative study was carried out between the JIS-D-5705 standard and the proposed method. Experimental results performed according to the JIS-D-5705 standard showed that all mirrors have a distortion lower than 5%, indicating that all meet the standard. On the other hand, the proposed method was able to detect that one of the mirrors presented an important distortion, which was not detected by the methodology proposed in the standard; therefore, that mirror should not meet the standard. Then, it was possible to conclude that the proposed distortion calculation method, based on image processing, has higher robustness and precision than the standard. In addition, an appropriate and effective behavior against changes in scale, resolution, and, unlike the standard, against changes in image rotation was also shown.

Analysis of the potential impact of strabismus with and without amblyopia on visual-perceptual and visual-motor skills evaluated using TVPS-3 and VMI-6 tests.

PURPOSE: To investigate the potential impact of strabismus and amblyopia on visual-perceptual skills (VPS) and visual-motor skills (VMS) of patients according to the type of strabismus, visual acuity (VA), state of binocularity, and sex. METHODS: This observational, transverse, prospective study analyzed a sample of 146 children with strabismus (88 male and 58 female) aged 5-15 years from Querétaro, México. To determine the strabismus type, we considered the deviation direction, frequency, binocularity state, and associated and dissociated elements. VPS and VMS were evaluated using the Test of Visual-Perceptual Skills 3rd ed. (TVPS-3) and Visual-Motor Integration Test of Beery 6th ed. (VMI-6). RESULTS: Sex was the main variable associated with the performance of the analyzed patients on TVPS-3 and VMI-6 (p<0.05); boys obtained better scores than girls in all evaluated aspects. Stereopsis was not a determinant of the patients' performance level but was associated with the far and near angles of deviation in both types of strabismus, esotropia and exotropia. Amblyopia was associated with the spatial relationship (p=0.001) and visual closure abilities (p=0.044). Form constancy skill scores diminished in both types of strabismus (esotropia: p=0.011; exotropia: p=0.004), and VMS were the most affected in patients with strabismus. CONCLUSIONS: The performance of patients with strabismus with and without amblyopia on TVPS-3 and VMI-6 suggests that they adopt a mechanism to compensate for the impact of strabismus on their VPS and VMS.