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Background: Pressure ulcers have become subject of study in recent years due to the treatment high costs and decreased life quality from patients. These chronic wounds are related to the global life expectancy increment, being the geriatric and physical disable patients the principal affected by this condition. Injuries diagnosis and treatment usually takes weeks or even months by medical personel. Using non-invasive techniques, such as image processing techniques, it is possible to conduct an analysis from ulcers and aid in its diagnosis. Methods: This paper proposes a novel technique for image segmentation based on contrast changes by using synthetic frequencies obtained from the grayscale value available in each pixel of the image. These synthetic frequencies are calculated using the model of energy density over an electric field to describe a relation between a constant density and the image amplitude in a pixel. A toroidal geometry is used to decompose the image into different contrast levels by variating the synthetic frequencies. Then, the decomposed image is binarized applying Otsu's threshold allowing for obtaining the contours that describe the contrast variations. Morphological operations are used to obtain the desired segment of the image. Results: The proposed technique is evaluated by synthesizing a Data Base with 51 images of pressure ulcers, provided by the Centre IGURCO. With the segmentation of these pressure ulcer images it is possible to aid in its diagnosis and treatment. To provide evidences of technique performance, digital image correlation was used as a measure, where the segments obtained using the methodology are compared with the real segments. The proposed technique is compared with two benchmarked algorithms. The results over the technique present an average correlation of 0.89 with a variation of ±0.1 and a computational time of 9.04 seconds. Conclusions: The methodology presents better segmentation results than the benchmarked algorithms using less computational time and without the need of an initial condition. [ABSTRACT FROM AUTHOR]

Background: One of the most critical tasks when conducting neurological studies is identifying the different regions of interest in the brain’s white matter. Currently few programs or applications are available that serve as an interactive guide in this process. This is why a mobile application has been designed and developed in order to teach users how to identify the referred regions of the brain. It also enables users to share the results obtained and take an examination on the knowledge thus learnt. In order to provide direct user-user or user-developer contact, the project includes a website and a Twitter account. Results: An application has been designed with a basic, minimalist look, which anyone can access easily in order to learn to identify a specific region in the brain’s white matter. A survey has also been conducted on people who have used it, which has shown that the application is attractive both in the student (final mean satisfaction of 4.2/5) and in the professional (final mean satisfaction of 4.3/5) environment. The response obtained in the online part of the project reflects the high practical value and quality of the application, as shown by the fact that the website has seen a large number of visitors (over 1000 visitors) and the Twitter account has a high number of followers (over 280 followers). Conclusions: Mobile NBM is the first mobile application to be used as a guide in the process of identifying a region of interest in the brain’s white matter. Although initially not many areas are available in the application, new ones can be added as required by users in their respective studies. Apart from the application itself, the online resources provided (website and Twitter account) significantly enhance users’ experience. [ABSTRACT FROM AUTHOR]

Background: Structural white matter abnormalities in pain-modulating, regions are present in migraine. Whether they are associated with pain chronification and with cognitive reserve is unclear., Methods: Prospective, cohort, six-month study of adult patients with episodic or chronic migraine, and controls. Cognitive reserve, quality of life, impact of pain on daily living, depression and anxiety were assessed. Participants underwent a diffusion-tensor MRI to establish the integrity of white matter tracts of three regions of interest (ROIs) implicated in pain modulation, emotion, cognition and resilience (anterior insula, anterior cingulate gyrus, and uncinate fasciculus)., Results: Fifty-two individuals were enrolled: 19 episodic migraine patients, 18 chronic migraine patients, and 15 controls. The analysis of the fractional anisotropy in the ROIs showed that those patients with the poorest prognosis (i.e., those with chronic migraine despite therapy at six months--long-term chronic migraneurs) had a significantly lower fractional anisotropy in the right ROIs. Participants with higher cognitive reserve also had greater fractional anisotropy in the right anterior insula and both cingulate gyri. Multivariate analysis showed a significant association between cognitive reserve, migraine frequency, and fractional anisotropy in the right-sided regions of interest., Conclusions: Long-term chronic migraine patients show abnormalities in anterior white matter tracts, particularly of the right hemisphere, involved in pain modulation emotion, cognition and resilience. Robustness in these areas is associated with a higher cognitive reserve, which in turn might result in a lower tendency to migraine chronification.