Performing PET/CT studies: do they create anxiety?

Introduction: Anxiety is a common problem in primary care and specialty medical settings. Treating an anxious patient takes more time and adds stress to staff. Unrecognised anxiety may lead to exam repetition, image artifacts and hinder the scan performance. Reducing patient anxiety at the onset is probably the most useful means of minimizing artifactual FDG uptake, both fat brown and skeletal muscle uptake, as well patient movement and claustrophobia. The aim of the study was to examine the effects of information giving on the anxiety levels of patients who are to undergo a PET/CT and whether the patient experience is enhanced with the creation of a guideline. Methodology: Two hundred and thirty two patients were given two questionnaires before and after the procedure to determine their prior knowledge, concerns, expectations and experiences about the study. Verbal information was given by one of the technologists after the completion of the first questionnaire. Results: Our results show that the main causes of anxiety in patients who are having a PET/CT is the fear of the procedure itself, and fear of the results. The patients who suffered from greater anxiety were those who were scanned during the initial stage of a disease. No significant differences were found between the anxiety levels pre procedural and post procedural. Findings with regard to satisfaction show us that the amount of information given before the procedure does not change the anxiety levels and therefore, does not influence patient satisfaction. Conclusions: The performance of a PET/CT scan is an important and statistically generator of anxiety. PET/CT patients are often poorly informed and present with a range of anxieties that may ultimately affect examination quality. The creation of a guideline may reduce the stress of not knowing what will happen, the anxiety created and may increase their satisfaction in the experience of having a PET/CT scan.

In-plane displacement and strain image analysis

Measurements in civil engineering load tests usually require considerable time and complex procedures. Therefore, measurements are usually constrained by the number of sensors resulting in a restricted monitored area. Image processing analysis is an alternative way that enables the measurement of the complete area of interest with a simple and effective setup. In this article photo sequences taken during load displacement tests were captured by a digital camera and processed with image correlation algorithms. Three different image processing algorithms were used with real images taken from tests using specimens of PVC and Plexiglas. The data obtained from the image processing algorithms were also compared with the data from physical sensors. A complete displacement and strain map were obtained. Results show that the accuracy of the measurements obtained by photogrammetry is equivalent to that from the physical sensors but with much less equipment and fewer setup requirements. © 2015Computer-Aided Civil and Infrastructure Engineering.

PINPIN a-Si: H based structures for X-ray image detection using the laser scanning technique

Conventional film based X-ray imaging systems are being replaced by their digital equivalents. Different approaches are being followed by considering direct or indirect conversion, with the later technique dominating. The typical, indirect conversion, X-ray panel detector uses a phosphor for X-ray conversion coupled to a large area array of amorphous silicon based optical sensors and a couple of switching thin film transistors (TFT). The pixel information can then be readout by switching the correspondent line and column transistors, routing the signal to an external amplifier. In this work we follow an alternative approach, where the electrical switching performed by the TFT is replaced by optical scanning using a low power laser beam and a sensing/switching PINPIN structure, thus resulting in a simpler device. The optically active device is a PINPIN array, sharing both front and back electrical contacts, deposited over a glass substrate. During X-ray exposure, each sensing side photodiode collects photons generated by the scintillator screen (560 nm), charging its internal capacitance. Subsequently a laser beam (445 nm) scans the switching diodes (back side) retrieving the stored charge in a sequential way, reconstructing the image. In this paper we present recent work on the optoelectronic characterization of the PINPIN structure to be incorporated in the X-ray image sensor. The results from the optoelectronic characterization of the device and the dependence on scanning beam parameters are presented and discussed. Preliminary results of line scans are also presented. (C) 2014 Elsevier B.V. All rights reserved.

A Força Aérea Portuguesa e o voo nas redes sociais

Trabalho de projeto apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Publicidade e Marketing.

FPGA-based architecture for hyperspectral unmixing

This paper proposes an FPGA-based architecture for onboard hyperspectral unmixing. This method based on the Vertex Component Analysis (VCA) has several advantages, namely it is unsupervised, fully automatic, and it works without dimensionality reduction (DR) pre-processing step. The architecture has been designed for a low cost Xilinx Zynq board with a Zynq-7020 SoC FPGA based on the Artix-7 FPGA programmable logic and tested using real hyperspectral datasets. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low cost embedded systems.

A toolbox for hyperspectral image analysis

This paper introduces a new toolbox for hyperspectral imagery, developed under the MATLAB environment. This toolbox provides easy access to different supervised and unsupervised classification methods. This new application is also versatile and fully dynamic since the user can embody their own methods, that can be reused and shared. This toolbox, while extends the potentiality of MATLAB environment, it also provides a user-friendly platform to assess the results of different methodologies. In this paper it is also presented, under the new application, a study of several different supervised and unsupervised classification methods on real hyperspectral data.