FOREWORD

oai:hrcak.srce.hr:

Adipose segmentation in small animals at 7T: a preliminary study

<p>Abstract</p> <p>Background</p> <p>Small animal MRI at 7 Tesla (T) provides a useful tool for adiposity research. For adiposity researchers, separation of fat from surrounding tissues and its subsequent quantitative or semi- quantitative analysis is a key task. This is a relatively new field and a priori it cannot be known which specific biological questions related to fat deposition will be relevant in a specific study. Thus it is impossible to predict what accuracy and what spatial resolution will be required in all cases and even difficult what accuracy and resolution will be useful in most cases. However the pragmatic time constraints and the practical resolution ranges are known for small animal imaging at 7T. Thus we have used known practical constraints to develop a method for fat volume analysis based on an optimized image acquisition and image post processing pair.</p> <p>Methods</p> <p>We designed a fat segmentation method based on optimizing a variety of factors relevant to small animal imaging at 7T. In contrast to most previously described MRI methods based on signal intensity of T1 weighted image alone, we chose to use parametric images based on Multi-spin multi-echo (MSME) Bruker pulse sequence which has proven to be particularly robust in our laboratory over the last several years. The sequence was optimized on a T1 basis to emphasize the signal. T2 relaxation times can be calculated from the multi echo data and we have done so on a pixel by pixel basis for the initial step in the post processing methodology. The post processing consists of parallel paths. On one hand, the weighted image is precisely divided into different regions with optimized smoothing and segmentation methods; and on the other hand, a confidence image is deduced from the parametric image according to the distribution of relaxation time relationship of typical adipose. With the assistance of the confidence image, a useful software feature was implemented to which enhances the data and in the end results in a more reliable and flexible method for adipose evaluation.</p> <p>Results</p> <p>In this paper, we describe how we arrived at our recommended procedures and key aspects of the post-processing steps. The feasibility of the proposed method is tested on both simulated and real data in this preliminary research. A research tool was created to help researchers segment out fat even when the anatomical information is of low quality making it difficult to distinguish between fat and non-fat. In addition, tool is designed to allow the operator to make adjustments to many of the key steps for comparison purposes and to quantitatively assess the difference these changes make. Ultimately our flexible software lets the researcher define key aspects of the fat segmentation and quantification.</p> <p>Conclusions</p> <p>Combining the full T2 parametric information with the optimized first echo image information, the research tool enhances the reliability of the results while providing more flexible operations than previous methods. The innovation in the method is to pair an optimized and very specific image acquisition technique to a flexible but tuned image post processing method. The separation of the fat is aided by the confidence distribution of regions produced on a scale relevant to and dictated by practical aspects of MRI at 7T.</p

ekoNET - Environmental Monitoring using Low-cost Sensors for Detecting Gases, Particulate Matter and Meteorological Parameters

This paper presents the environmental monitoring solution ekoNET, developed for a real-time monitoring of air pollution and other atmospheric condition parameters such as temperature, air pressure and humidity. The system is based on low-cost gas, PM and meteorological sensors providing cost-efficient, simple to deploy, use and maintain solution targeted for the usage within the Internet of Things domain of smart cities and smart enterprises. The paper gives an overview of the system architecture, encompassing the ekoNET device, back-end cloud infrastructure, data handling and visualization engine as well as the application-level components and modules. Furthermore, initial field trial data of twelve ekoNET devices is presented, enabling the overall system operation performance testing.International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing., 8th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS), Jul 02-04, 2014, Birmingham City Univ, Birmingham, Englan

Testing of gadolinium oxy-sulphide phosphors for use in CCD-based X-ray detectors for macromolecular crystallography

The resolution and detective quantum efficiency of CCD-based detectors used for X-ray diffraction is primarily affected by the layer of phosphor that converts incident X-ray photons into visible photons. The optimum thickness of this phosphor layer is strongly dependent on the fraction of absorbed incident X-ray photons and required spatial resolution. A range of terbium doped gadolinium oxy-sulphide (Gd2O2S:Tb) phosphor samples, provided by Applied Scintillation Technologies, have been evaluated for spatial resolution, light output and uniformity. The phosphor samples varied in coating weight (10-25 mg/cm2), grain size (2.5, 4, 10 ?m), and applied coating (no coating, reflectors and absorbers). In addition, a non-uniform layer was introduced to some samples in order to provide an inherent diffusion layer. The experimental results showed that the introduction of a reflector increases the point spread function (PSF) and increases light yield up to 30%, while an absorber reduces the PSF tails and decreases the light yield up to 35%. The PSF linearly increases with thickness, while the greatest light yield was obtained with phosphor samples of 4 ?m particle size. © 2002 Elsevier Science B.V. All rights reserved.</p