El blog y otras herramientas comunicativas de la biblioteca del Área de Gestión Sanitaria Este de Málaga - Axarquía

In 2006 the Library of the Andalusian Public Health System (BVSSPA) is constituted as a Virtual Library which provides Resources and Services that are accessed through inter-hospital local area network (corporate intranet) and Internet. On the other hand, the Hospital de la Axarquia still did not have any institutional or self-presence on the Internet and the librarian ask the need to create a space for communication with the "digital users" of the Library of the area through a website. MATERIALS AND METHODS. The reasons why we opted for a blog were: -It was necessary to make no financial outlay for its establishment. It allowed for great versatility, both in its administration and in its management by users. -The ability to compile on the same platform different Web 2.0 communication tools. Between different options available we chose Blogger Google Inc. The blog allowed entry to the 2.0 services or Social Web in the library. The benefits offered were many, especially the visibility of the service and communication with the user. 2.0 tools that have been incorporated into the library are: content syndication (RSS) which allowed users to stay informed about updates to the blog. Share documents and other multimedia as presentations through SlideShare, images through Flickr or Picasa, or videos (YouTube). And the presence on social network like Facebook and Twitter. RESULTS. The analysis of the activity we has been traking by Google Analytics tool, helping to determine the number of blog visits. Since its stablishment, on November 17th 2006, until November 29th 2010 the blog has received 15,787 visitors, 38,422 page views were consulted, at each visit on average 2.4 pages were consulted and each visit has an average stay at the site of 4'31''. DISCUSSION. The blog has served as a communication and information tool with the user. Since the creation of the blog we have incorporated technologies and tools to interact with the user. With all the tools used we have applied the concept of "open source" and the contents were generated from the activities organized in the Knowledge Management Unit from the anatomo-clinical sessions, the training activities, dissemination events, etc. The result has been the customization of library services, contextualized in the Knowledge Management Unit - Axarquia. In social networks we have shared information and files with the professionals and the community. CONCLUSIONS. The blog has allowed us to explore technologies that allow us to communicate with the user and the community, disseminate information and documents with the participation of users and become the "Interactive Library" we aspire to be.

Brain tissue segmentation of fetal MR images

We present a segmentation method for fetal brain tissuesof T2w MR images, based on the well known ExpectationMaximization Markov Random Field (EM- MRF) scheme. Ourmain contribution is an intensity model composed of 7Gaussian distribution designed to deal with the largeintensity variability of fetal brain tissues. The secondmain contribution is a 3-steps MRF model that introducesboth local spatial and anatomical priors given by acortical distance map. Preliminary results on 4 subjectsare presented and evaluated in comparison to manualsegmentations showing that our methodology cansuccessfully be applied to such data, dealing with largeintensity variability within brain tissues and partialvolume (PV).

Weighted Shape-based Averaging with Neighborhood Prior Model for Multiple Atlas Fusion-based Medical Image Segmentation

In medical imaging, merging automated segmentations obtained from multiple atlases has become a standard practice for improving the accuracy. In this letter, we propose two new fusion methods: "Global Weighted Shape-Based Averaging" (GWSBA) and "Local Weighted Shape-Based Averaging" (LWSBA). These methods extend the well known Shape-Based Averaging (SBA) by additionally incorporating the similarity information between the reference (i.e., atlas) images and the target image to be segmented. We also propose a new spatially-varying similarity-weighted neighborhood prior model, and an edge-preserving smoothness term that can be used with many of the existing fusion methods. We first present our new Markov Random Field (MRF) based fusion framework that models the above mentioned information. The proposed methods are evaluated in the context of segmentation of lymph nodes in the head and neck 3D CT images, and they resulted in more accurate segmentations compared to the existing SBA.

Atlas-based segmentation of pathological brain MR images

We propose a method for brain atlas deformation inpresence of large space-occupying tumors, based on an apriori model of lesion growth that assumes radialexpansion of the lesion from its starting point. First,an affine registration brings the atlas and the patientinto global correspondence. Then, the seeding of asynthetic tumor into the brain atlas provides a templatefor the lesion. Finally, the seeded atlas is deformed,combining a method derived from optical flow principlesand a model of lesion growth (MLG). Results show that themethod can be applied to the automatic segmentation ofstructures and substructures in brains with grossdeformation, with important medical applications inneurosurgery, radiosurgery and radiotherapy.

Determination of Transmembrane Water Fluxes in Neurons Elicited by Glutamate Ionotropic Receptors and by the Cotransporters KCC2 and NKCC1: A Digital Holographic Microscopy Study.

Digital holographic microscopy (DHM) is a noninvasive optical imaging technique that provides quantitative phase images of living cells. In a recent study, we showed that the quantitative monitoring of the phase signal by DHM was a simple label-free method to study the effects of glutamate on neuronal optical responses (Pavillon et al., 2010). Here, we refine these observations and show that glutamate produces the following three distinct optical responses in mouse primary cortical neurons in culture, predominantly mediated by NMDA receptors: biphasic, reversible decrease (RD) and irreversible decrease (ID) responses. The shape and amplitude of the optical signal were not associated with a particular cellular phenotype but reflected the physiopathological status of neurons linked to the degree of NMDA activity. Thus, the biphasic, RD, and ID responses indicated, respectively, a low-level, a high-level, and an "excitotoxic" level of NMDA activation. Moreover, furosemide and bumetanide, two inhibitors of sodium-coupled and/or potassium-coupled chloride movement strongly modified the phase shift, suggesting an involvement of two neuronal cotransporters, NKCC1 (Na-K-Cl) and KCC2 (K-Cl) in the genesis of the optical signal. This observation is of particular interest since it shows that DHM is the first imaging technique able to monitor dynamically and in situ the activity of these cotransporters during physiological and/or pathological neuronal conditions.

Atlas-based segmentation of pathological MR brain images using a model of lesion growth.

We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.

Noninvasive characterization of the fission yeast cell cycle by monitoring dry mass with digital holographic microscopy.

Digital holography microscopy (DHM) is an optical technique which provides phase images yielding quantitative information about cell structure and cellular dynamics. Furthermore, the quantitative phase images allow the derivation of other parameters, including dry mass production, density, and spatial distribution. We have applied DHM to study the dry mass production rate and the dry mass surface density in wild-type and mutant fission yeast cells. Our study demonstrates the applicability of DHM as a tool for label-free quantitative analysis of the cell cycle and opens the possibility for its use in high-throughput screening.

Feature Extraction from Whole-Sky Ground-Based Images for Cloud-Type Recognition

Several features that can be extracted from digital images of the sky and that can be useful for cloud-type classification of such images are presented. Some features are statistical measurements of image texture, some are based on the Fourier transform of the image and, finally, others are computed from the image where cloudy pixels are distinguished from clear-sky pixels. The use of the most suitable features in an automatic classification algorithm is also shown and discussed. Both the features and the classifier are developed over images taken by two different camera devices, namely, a total sky imager (TSI) and a whole sky imager (WSC), which are placed in two different areas of the world (Toowoomba, Australia; and Girona, Spain, respectively). The performance of the classifier is assessed by comparing its image classification with an a priori classification carried out by visual inspection of more than 200 images from each camera. The index of agreement is 76% when five different sky conditions are considered: clear, low cumuliform clouds, stratiform clouds (overcast), cirriform clouds, and mottled clouds (altocumulus, cirrocumulus). Discussion on the future directions of this research is also presented, regarding both the use of other features and the use of other classification techniques

A Motion compensated filtering approach to remove sunlight flicker in shallow water images

A common problem in video surveys in very shallow waters is the presence of strong light fluctuations, due to sun light refraction. Refracted sunlight casts fast moving patterns, which can significantly degrade the quality of the acquired data. Motivated by the growing need to improve the quality of shallow water imagery, we propose a method to remove sunlight patterns in video sequences. The method exploits the fact that video sequences allow several observations of the same area of the sea floor, over time. It is based on computing the image difference between a given reference frame and the temporal median of a registered set of neighboring images. A key observation is that this difference will have two components with separable spectral content. One is related to the illumination field (lower spatial frequencies) and the other to the registration error (higher frequencies). The illumination field, recovered by lowpass filtering, is used to correct the reference image. In addition to removing the sunflickering patterns, an important advantage of the approach is the ability to preserve the sharpness in corrected image, even in the presence of registration inaccuracies. The effectiveness of the method is illustrated in image sets acquired under strong camera motion containing non-rigid benthic structures. The results testify the good performance and generality of the approach

An Efficient Segmentation Method for Ultrasound Images based on a Semi-supervised Approach and Patch-based Features

Segmenting ultrasound images is a challenging problemwhere standard unsupervised segmentation methods such asthe well-known Chan-Vese method fail. We propose in thispaper an efficient segmentation method for this class ofimages. Our proposed algorithm is based on asemi-supervised approach (user labels) and the use ofimage patches as data features. We also consider thePearson distance between patches, which has been shown tobe robust w.r.t speckle noise present in ultrasoundimages. Our results on phantom and clinical data show avery high similarity agreement with the ground truthprovided by a medical expert.

Measurement of absolute cell volume, osmotic membrane water permeability, and refractive index of transmembrane water and solute flux by digital holographic microscopy.

ABSTRACT. A dual-wavelength digital holographic microscope to measure absolute volume of living cells is proposed. The optical setup allows us to reconstruct two quantitative phase contrast images at two different wavelengths from a single hologram acquisition. When adding the absorbing dye fast green FCF as a dispersive agent to the extracellular medium, cellular thickness can be univocally determined in the full field of view. In addition to the absolute cell volume, the method can be applied to derive important biophysical parameters of living cells including osmotic membrane water permeability coefficient and the integral intracellular refractive index (RI). Further, the RI of transmembrane flux can be determined giving an indication about the nature of transported solutes. The proposed method is applied to cultured human embryonic kidney cells, Chinese hamster ovary cells, human red blood cells, mouse cortical astrocytes, and neurons.

Multi-Atlas based Segmentation of Head and Neck CT Images using Active Contour

This paper presents the segmentation of bilateral parotid glands in the Head and Neck (H&N) CT images using an active contour based atlas registration. We compare segmentation results from three atlas selection strategies: (i) selection of "single-most-similar" atlas for each image to be segmented, (ii) fusion of segmentation results from multiple atlases using STAPLE, and (iii) fusion of segmentation results using majority voting. Among these three approaches, fusion using majority voting provided the best results. Finally, we present a detailed evaluation on a dataset of eight images (provided as a part of H&N auto segmentation challenge conducted in conjunction with MICCAI-2010 conference) using majority voting strategy.

Multifractal wavelet filter of natural images

Natural images are characterized by the multiscaling properties of their contrast gradient, in addition to their power spectrum. In this Letter we show that those properties uniquely define an intrinsic wavelet and present a suitable technique to obtain it from an ensemble of images. Once this wavelet is known, images can be represented as expansions in the associated wavelet basis. The resulting code has the remarkable properties that it separates independent features at different resolution level, reducing the redundancy, and remains essentially unchanged under changes in the power spectrum. The possible generalization of this representation to other systems is discussed.

Multiple Geotechnological Tools Applied to Digital Mapping of Tropical Soils

ABSTRACT In recent years, geotechnologies as remote and proximal sensing and attributes derived from digital terrain elevation models indicated to be very useful for the description of soil variability. However, these information sources are rarely used together. Therefore, a methodology for assessing and specialize soil classes using the information obtained from remote/proximal sensing, GIS and technical knowledge has been applied and evaluated. Two areas of study, in the State of São Paulo, Brazil, totaling approximately 28.000 ha were used for this work. First, in an area (area 1), conventional pedological mapping was done and from the soil classes found patterns were obtained with the following information: a) spectral information (forms of features and absorption intensity of spectral curves with 350 wavelengths -2,500 nm) of soil samples collected at specific points in the area (according to each soil type); b) obtaining equations for determining chemical and physical properties of the soil from the relationship between the results obtained in the laboratory by the conventional method, the levels of chemical and physical attributes with the spectral data; c) supervised classification of Landsat TM 5 images, in order to detect changes in the size of the soil particles (soil texture); d) relationship between classes relief soils and attributes. Subsequently, the obtained patterns were applied in area 2 obtain pedological classification of soils, but in GIS (ArcGIS). Finally, we developed a conventional pedological mapping in area 2 to which was compared with a digital map, ie the one obtained only with pre certain standards. The proposed methodology had a 79 % accuracy in the first categorical level of Soil Classification System, 60 % accuracy in the second category level and became less useful in the categorical level 3 (37 % accuracy).