Laser scanned photodiodes (LSPs) for image sensing

An optimized ZnO:Al/a-pin SixC1-x:H/Al configuration for the laser scanned photodiode (LSP) imaging detector is proposed and the read-out parameters improved. The effect of the sensing element structure, cell configuration and light source flux are investigated and correlated with the sensor output characteristics. Data reveals that for sensors with wide band gap doped layers an increase on the image signal optimized to the blue is achieved with a dynamic range of two orders of magnitude, a responsivity of 6 mA W-1 and a sensitivity of 17 muW cm(-2) at 530 nm. The main output characteristics such as image responsivity, resolution, linearity and dynamic range were analyzed under reverse, forward and short circuit modes. The results show that the sensor performance can be optimized in short circuit mode. A trade-off between the scan time and the required resolution is needed since the spot size limits the resolution due to the cross-talk between dark and illuminated regions leading to blurring effects.

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.

Spatio-temporal alignment of pedobarographic image sequences

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

Methods for automatic and assisted image annotation

Personal memories composed of digital pictures are very popular at the moment. To retrieve these media items annotation is required. During the last years, several approaches have been proposed in order to overcome the image annotation problem. This paper presents our proposals to address this problem. Automatic and semi-automatic learning methods for semantic concepts are presented. The automatic method is based on semantic concepts estimated using visual content, context metadata and audio information. The semi-automatic method is based on results provided by a computer game. The paper describes our proposals and presents their evaluations.

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.

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.

10 kVp rule – An anthropomorphic pelvis phantom imaging study using a CR system: impact on image quality and effective dose using AEC and manual mode

Purpose - This study aims to investigate the influence of tube potential (kVp) variation in relation to perceptual image quality and effective dose (E) for pelvis using automatic exposure control (AEC) and non-AEC in a Computed Radiography (CR) system. Methods and materials - To determine the effects of using AEC and non-AEC by applying the 10 kVp rule in two experiments using an anthropomorphic pelvis phantom. Images were acquired using 10 kVp increments (60–120 kVp) for both experiments. The first experiment, based on seven AEC combinations, produced 49 images. The mean mAs from each kVp increment were used as a baseline for the second experiment producing 35 images. A total of 84 images were produced and a panel of 5 experienced observers participated for the image scoring using the two alternative forced choice (2AFC) visual grading software. PCXMC software was used to estimate E. Results - A decrease in perceptual image quality as the kVp increases was observed both in non-AEC and AEC experiments, however no significant statistical differences (p > 0.05) were found. Image quality scores from all observers at 10 kVp increments for all mAs values using non-AEC mode demonstrates a better score up to 90 kVp. E results show a statistically significant decrease (p = 0.000) on the 75th quartile from 0.37 mSv at 60 kVp to 0.13 mSv at 120 kVp when applying the 10 kVp rule in non-AEC mode. Conclusion - Using the 10 kVp rule, no significant reduction in perceptual image quality is observed when increasing kVp whilst a marked and significant E reduction is observed.

Hyperspectral subspace identification

Signal subspace identification is a crucial first step in many hyperspectral processing algorithms such as target detection, change detection, classification, and unmixing. The identification of this subspace enables a correct dimensionality reduction, yielding gains in algorithm performance and complexity and in data storage. This paper introduces a new minimum mean square error-based approach to infer the signal subspace in hyperspectral imagery. The method, which is termed hyperspectral signal identification by minimum error, is eigen decomposition based, unsupervised, and fully automatic (i.e., it does not depend on any tuning parameters). It first estimates the signal and noise correlation matrices and then selects the subset of eigenvalues that best represents the signal subspace in the least squared error sense. State-of-the-art performance of the proposed method is illustrated by using simulated and real hyperspectral images.

Does independent component analysis play a role in unmixing hyperspectral data?

Independent component analysis (ICA) has recently been proposed as a tool to unmix hyperspectral data. ICA is founded on two assumptions: 1) the observed spectrum vector is a linear mixture of the constituent spectra (endmember spectra) weighted by the correspondent abundance fractions (sources); 2)sources are statistically independent. Independent factor analysis (IFA) extends ICA to linear mixtures of independent sources immersed in noise. Concerning hyperspectral data, the first assumption is valid whenever the multiple scattering among the distinct constituent substances (endmembers) is negligible, and the surface is partitioned according to the fractional abundances. The second assumption, however, is violated, since the sum of abundance fractions associated to each pixel is constant due to physical constraints in the data acquisition process. Thus, sources cannot be statistically independent, this compromising the performance of ICA/IFA algorithms in hyperspectral unmixing. This paper studies the impact of hyperspectral source statistical dependence on ICA and IFA performances. We conclude that the accuracy of these methods tends to improve with the increase of the signature variability, of the number of endmembers, and of the signal-to-noise ratio. In any case, there are always endmembers incorrectly unmixed. We arrive to this conclusion by minimizing the mutual information of simulated and real hyperspectral mixtures. The computation of mutual information is based on fitting mixtures of Gaussians to the observed data. A method to sort ICA and IFA estimates in terms of the likelihood of being correctly unmixed is proposed.

Vertex component analysis: a fast algorithm to unmix hyperspectral data

Given a set of mixed spectral (multispectral or hyperspectral) vectors, linear spectral mixture analysis, or linear unmixing, aims at estimating the number of reference substances, also called endmembers, their spectral signatures, and their abundance fractions. This paper presents a new method for unsupervised endmember extraction from hyperspectral data, termed vertex component analysis (VCA). The algorithm exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. In a series of experiments using simulated and real data, the VCA algorithm competes with state-of-the-art methods, with a computational complexity between one and two orders of magnitude lower than the best available method.