Novel structure for large area image sensing

This work presents preliminary results in the study of a novel structure for a laser scanned photodiode (LSP) type of image sensor. In order to increase the signal output, a stacked p-i-n-p-i-n structure with an intermediate light-blocking layer is used. The image and the scanning beam are incident through opposite sides of the sensor and their absorption is kept in separate junctions by an intermediate light-blocking layer. As in the usual LSP structure the scanning beam-induced photocurrent is dependent on the local illumination conditions of the image. The main difference between the two structures arises from the fact that in this new structure the image and the scanner have different optical paths leading to an increase in the photocurrent when the scanning beam is incident on a region illuminated on the image side of the sensor, while a decreasing in the photocurrent was observed in the single junction LSP. The results show that the structure can be successfully used as an image sensor even though some optimization is needed to enhance the performance of the device.

Supermarkets in Portugal: corporate social responsibility image, attitude towards the brand and purchase intention

Recently, companies developed strategies which may influence their Corporate Social Responsibility (CSR) image. This paper discusses the image of four different supermarkets with stores in Portugal. The research compares CSR image and brand attitude of the four supermarkets. Empirical evidence shows that different supermarkets belonging to the same company have different CSR image and brand attitude. The research also confirms that there is positive correlation between CSR image and attitude towards the brand. Further, the results offer empirical evidence that CSR image and brand attitude influence purchase intention of supermarket brands. Finally, brand purchase intention is highly influenced by attitude towards the brand than CSR image.

Image quality in diagnostic radiology

This chapter provides a theoretical background about image quality in diagnostic radiology. Digital image representation and also image quality evaluation methods are here discussed. An overview of methods for quality evaluation of diagnostic imaging procedures is provided. Digital image representation and primary physical image quality parameters are also discussed, including objective image quality measurements and observer performance methods.

Image enhancement for digital radiography

Once in a digital form, a radiographic image may be processed in several ways in order to turn the visualization an act of improved diagnostic value. Practitioners should be aware that, depending on each clinical context, digital image processing techniques are available to help to unveil visual information that is, in fact, carried by the bare digital radiograph and may be otherwise neglected. The range of visual enhancement procedures includes simple techniques that deal with the usual brightness and contrast manipulation up to much more elaborate multi-scale processing that provides customized control over the emphasis given to the relevant finer anatomical details. This chapter is intended to give the reader a practical understanding of image enhancement techniques that might be helpful to improve the visual quality of the digital radiographs and thus to contribute to a more reliable and assertive reporting.

Towards an efficient and robust foot classification from pedobarographic images

O documento em anexo encontra-se na versão post-print (versão corrigida pelo editor).

Spatio-temporal alignment of pedobarographic image sequences

O documento em anexo encontra-se na versão post-print (versão corrigida pelo editor).

Adaptive tool for automatic data collection of real electricity markets

The study of electricity markets operation has been gaining an increasing importance in last years, as result of the new challenges that the electricity markets restructuring produced. This restructuring increased the competitiveness of the market, but with it its complexity. The growing complexity and unpredictability of the market’s evolution consequently increases the decision making difficulty. Therefore, the intervenient entities are forced to rethink their behaviour and market strategies. Currently, lots of information concerning electricity markets is available. These data, concerning innumerous regards of electricity markets operation, is accessible free of charge, and it is essential for understanding and suitably modelling electricity markets. This paper proposes a tool which is able to handle, store and dynamically update data. The development of the proposed tool is expected to be of great importance to improve the comprehension of electricity markets and the interactions among the involved entities.

Image quality of myocardial perfusion-gated studies: effect of ingestion of different fat content in the reduction of extra-myocardial abdominal signal

Myocardial perfusion-gated-SPECT (MP-gated-SPECT) imaging often shows radiotracer uptake in abdominal organs. This accumulation interferes frequently with qualitative and quantitative assessment of the infero-septal region of myocardium. The objective of this study is to evaluate the effect of ingestion of different fat content on the reduction of extra-myocardial uptake and to improve MP-gated-SPECT image quality. In this study, 150 patients (65 ^ 18 years) who were referred for MP-gated-SPECT underwent a 1-day-protocol including imaging after stress (physical or pharmacological) and resting conditions. All patients gave written informed consent. Patients were subdivided into five groups: GI, GII, GIII, GIV and GV. In the first four groups, patients ate two chocolate bars with different fat content. Patients in GV – control group (CG) – had just water. Uptake indices (UI) of myocardium (M)/liver(L) and M/stomach–proximal bowel(S) revealed lower UI of M/S at rest in all groups. Both stress and rest studies using different food intake indicate that patients who ate chocolate with different fat content showed better UI of M/L than the CG. The UI of M/L and M/S of groups obtained under physical stress are clearly superior to that of groups obtained under pharmacological stress. These differences are only significant in patients who ate high-fat chocolate or drank water. The analysis of all stress studies together (GI, GII, GIII and GIV) in comparison with CG shows higher mean ranks of UI of M/L for those who ate high-fat chocolate. After pharmacological stress, the mean ranks of UI of M/L were higher for patients who ate high- and low-fat chocolate. In conclusion, eating food with fat content after radiotracer injection increases, respectively, the UI of M/L after stress and rest in MP-gated-SPECT studies. It is, therefore, recommended that patients eat a chocolate bar after radiotracer injection and before image acquisition.

Analysis and simulation of a-Si Ha-SiC HPINIP structures for color image detection

It is presented in this paper a study on the photo-electronic properties of multi layer a-Si: H/a-SiC: H p-i-n-i-p structures. This study is aimed to give an insight into the internal electrical characteristics of such a structure in thermal equilibrium, under applied Was and under different illumination condition. Taking advantage of this insight it is possible to establish a relation among-the electrical behavior of the structure the structure geometry (i.e. thickness of the light absorbing intrinsic layers and of the internal n-layer) and the composition of the layers (i.e. optical bandgap controlled through percentage of carbon dilution in the a-Si1-xCx: H layers). Showing an optical gain for low incident light power controllable by means of externally applied bias or structure composition, these structures are quite attractive for photo-sensing device applications, like color sensors and large area color image detector. An analysis based on numerical ASCA simulations is presented for describing the behavior of different configurations of the device and compared with experimental measurements (spectral response and current-voltage characteristic). (c) 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automatic vehicle detection and classification

This paper presents a proposal for an automatic vehicle detection and classification (AVDC) system. The proposed AVDC should classify vehicles accordingly to the Portuguese legislation (vehicle height over the first axel and number of axels), and should also support profile based classification. The AVDC should also fulfill the needs of the Portuguese motorway operator, Brisa. For the classification based on the profile we propose:he use of Eigenprofiles, a technique based on Principal Components Analysis. The system should also support multi-lane free flow for future integration in this kind of environments.

The usefulness of ultrasound in the classification of chronic liver disease

Chronic Liver Disease is a progressive, most of the time asymptomatic, and potentially fatal disease. In this paper, a semi-automatic procedure to stage this disease is proposed based on ultrasound liver images, clinical and laboratorial data. In the core of the algorithm two classifiers are used: a k nearest neighbor and a Support Vector Machine, with different kernels. The classifiers were trained with the proposed multi-modal feature set and the results obtained were compared with the laboratorial and clinical feature set. The results showed that using ultrasound based features, in association with laboratorial and clinical features, improve the classification accuracy. The support vector machine, polynomial kernel, outperformed the others classifiers in every class studied. For the Normal class we achieved 100% accuracy, for the chronic hepatitis with cirrhosis 73.08%, for compensated cirrhosis 59.26% and for decompensated cirrhosis 91.67%.

Fatty liver characterization and classification by ultrasound

Steatosis, also known as fatty liver, corresponds to an abnormal retention of lipids within the hepatic cells and reflects an impairment of the normal processes of synthesis and elimination of fat. Several causes may lead to this condition, namely obesity, diabetes, or alcoholism. In this paper an automatic classification algorithm is proposed for the diagnosis of the liver steatosis from ultrasound images. The features are selected in order to catch the same characteristics used by the physicians in the diagnosis of the disease based on visual inspection of the ultrasound images. The algorithm, designed in a Bayesian framework, computes two images: i) a despeckled one, containing the anatomic and echogenic information of the liver, and ii) an image containing only the speckle used to compute the textural features. These images are computed from the estimated RF signal generated by the ultrasound probe where the dynamic range compression performed by the equipment is taken into account. A Bayes classifier, trained with data manually classified by expert clinicians and used as ground truth, reaches an overall accuracy of 95% and a 100% of sensitivity. The main novelties of the method are the estimations of the RF and speckle images which make it possible to accurately compute textural features of the liver parenchyma relevant for the diagnosis.

3D-2D image registration by nonlinear regression

We propose a 3D-2D image registration method that relates image features of 2D projection images to the transformation parameters of the 3D image by nonlinear regression. The method is compared with a conventional registration method based on iterative optimization. For evaluation, simulated X-ray images (DRRs) were generated from coronary artery tree models derived from 3D CTA scans. Registration of nine vessel trees was performed, and the alignment quality was measured by the mean target registration error (mTRE). The regression approach was shown to be slightly less accurate, but much more robust than the method based on an iterative optimization approach.

Image upsampling algorithms applied on Nuclear Medicine: comparision of hqnx and nxSaI algorithms families with two interpolation algorithms - nearest neighbour and bicubic interpolation

Introduction: Image resizing is a normal feature incorporated into the Nuclear Medicine digital imaging. Upsampling is done by manufacturers to adequately fit more the acquired images on the display screen and it is applied when there is a need to increase - or decrease - the total number of pixels. This paper pretends to compare the “hqnx” and the “nxSaI” magnification algorithms with two interpolation algorithms – “nearest neighbor” and “bicubic interpolation” – in the image upsampling operations. Material and Methods: Three distinct Nuclear Medicine images were enlarged 2 and 4 times with the different digital image resizing algorithms (nearest neighbor, bicubic interpolation nxSaI and hqnx). To evaluate the pixel’s changes between the different output images, 3D whole image plot profiles and surface plots were used as an addition to the visual approach in the 4x upsampled images. Results: In the 2x enlarged images the visual differences were not so noteworthy. Although, it was clearly noticed that bicubic interpolation presented the best results. In the 4x enlarged images the differences were significant, with the bicubic interpolated images presenting the best results. Hqnx resized images presented better quality than 4xSaI and nearest neighbor interpolated images, however, its intense “halo effect” affects greatly the definition and boundaries of the image contents. Conclusion: The hqnx and the nxSaI algorithms were designed for images with clear edges and so its use in Nuclear Medicine images is obviously inadequate. Bicubic interpolation seems, from the algorithms studied, the most suitable and its each day wider applications seem to show it, being assumed as a multi-image type efficient algorithm.

Quality assurance and quality control in mammography: a review of available guidance worldwide

Objectives - Review available guidance for quality assurance (QA) in mammography and discuss its contribution to harmonise practices worldwide. Methods - Literature search was performed on different sources to identify guidance documents for QA in mammography available worldwide in international bodies, healthcare providers, professional/scientific associations. The guidance documents identified were reviewed and a selection was compared for type of guidance (clinical/technical), technology and proposed QA methodologies focusing on dose and image quality (IQ) performance assessment. Results - Fourteen protocols (targeted at conventional and digital mammography) were reviewed. All included recommendations for testing acquisition, processing and display systems associated with mammographic equipment. All guidance reviewed highlighted the importance of dose assessment and testing the Automatic Exposure Control (AEC) system. Recommended tests for assessment of IQ showed variations in the proposed methodologies. Recommended testing focused on assessment of low-contrast detection, spatial resolution and noise. QC of image display is recommended following the American Association of Physicists in Medicine guidelines. Conclusions - The existing QA guidance for mammography is derived from key documents (American College of Radiology and European Union guidelines) and proposes similar tests despite the variations in detail and methodologies. Studies reported on QA data should provide detail on experimental technique to allow robust data comparison. Countries aiming to implement a mammography/QA program may select/prioritise the tests depending on available technology and resources.