A survey in Portuguese X-ray fluoroscopy equipment: dose rates and image quality

X-ray fluoroscopy is essential in both diagnosis and medical intervention, although it may contribute to significant radiation doses to patients that have to be optimised and justified. Therefore, it is crucial to the patient to be exposed to the lowest achievable dose without compromising the image quality. The purpose of this study was to perform an analysis of the quality control measurements, particularly dose rates, contrast and spatial resolution of Portuguese fluoroscopy equipment and also to provide a contribution to the establishment of reference levels for the equipment performance parameters. Measurements carried out between 2007 and 2013 on 143 fluoroscopy equipment distributed by 34 nationwide health units were analysed. The measurements suggest that image quality and dose rates of Portuguese equipment are congruent with other studies, and in general, they are as per the Portuguese law. However, there is still a possibility of improvements intending optimisation at a national level.

Automatic tunning of Okumura-Hata model on railway communications

This paper presents the Genetic Algorithms (GA) as an efficient solution for the Okumura-Hata prediction model tuning on railways communications. A method for modelling the propagation model tuning parameters was presented. The algorithm tuning and validation were based on real networks measurements carried out on four different propagation scenarios and several performance indicators were used. It was shown that the proposed GA is able to produce significant improvements over the original model. The algorithm developed is currently been used on real GSM-R network planning process for an enhanced resources usage.

Fatty liver automatic diagnosis from ultrasound images

In this paper an automatic classification algorithm is proposed for the diagnosis of the liver steatosis, also known as, fatty liver, from ultrasound images. The features, automatically extracted from the ultrasound images used by the classifier, are basically the ones used by the physicians in the diagnosis of the disease based on visual inspection of the ultrasound images. The main novelty of the method is the utilization of the speckle noise that corrupts the ultrasound images to compute textural features of the liver parenchyma relevant for the diagnosis. The algorithm uses the Bayesian framework to compute a noiseless image, containing anatomic and echogenic information of the liver and a second image containing only the speckle noise used to compute the textural features. The classification results, with the Bayes classifier using manually classified data as ground truth show that the automatic classifier reaches an accuracy of 95% and a 100% of sensitivity.

Reversible current power supply for fast-field cycling nuclear magnetic resonance equipment

The Fast Field-Cycling Nuclear Magnetic Resonance (FFC-NMR) is a technique used to study the molecular dynamics of different types of materials. The main elements of this equipment are a magnet and its power supply. The magnet used as reference in this work is basically a ferromagnetic core with two sets of coils and an air-gap where the materials' sample is placed. The power supply should supply the magnet being the magnet current controlled in order to perform cycles. One of the technical issues of this type of solution is the compensation of the non-linearities associated to the magnetic characteristic of the magnet and to parasitic magnetic fields. To overcome this problem, this paper describes and discusses a solution for the FFC-NMR power supply based on a four quadrant DC/DC converter.