Balayage visuel des sujets effectuant l'auto-évaluation de l'échelle ELADEB

Introduction Les Echelles Lausannoises d'Auto-Evaluation des Difficultés et des Besoins ELADEB, est un outil utilisé en réhabilitation psychiatrique permettant de dresser le profil des problèmes rencontrés par les patients psychiatriques dans les principaux domaines de la vie quotidienne, ainsi que le besoin d'aide supplémentaire à celle déjà existante. Cet outil a déjà été validé dans une étude1 portant sur 94 patients et recueille un intérêt grandissant. Afin de compléter les données de validation recueillies lors de la première étude, nous présentons ici une seconde étude visant à comprendre d'avantage cet outil en le couplant à l'Eye tracker qui permet une étude du regard et ainsi observer des phénomènes visuels des sujets qui pratiquent l'auto-évaluation des difficultés et des besoins d'aide. Objectifs Cette étude pilote et exploratrice a pour but de mesurer l'exploration visuelle des cartes lors de l'évaluation d'ELADEB au travers des trois variables suivantes d'oculométrie récoltées au travers de l'outil de mesure de l'Eye tracker : (1) la variation de la taille pupillaire (pixels), (2) le rapport des nombres de points de fixation/temps, et (3) de la durée totale du temps de traitement de l'information de la carte (ms). Hypothèses. Le traitement visuel des cartes sélectionnées comme problèmes versus non problèmes sera différent chez tout le monde d'une part au niveau de : (1) la variation pupillaire, (2) du nombre de points de fixation de l'oeil/temps ainsi que (3) de la durée totale du traitement de l'information de la carte en fonction de notre compréhension. On peut poser l'hypothèse que l'émotion sera différente selon que la personne rencontre un problème ou non et ainsi, on peut s'attendre à ce que les cartes sélectionnées comme problèmes soient associées à une réaction émotionnelle plus importante que les autres, ce qui nous permettrait d'observer une corrélation entre le balayage visuel et ELADEB. Méthodes Cette étude exploratoire porte sur un échantillon de 10 sujets passant un test d'évaluation des difficultés et des besoins ELADEB, couplé à un appareil d'Eye tracking. Les critères d'inclusion des sujets sont : (1) hommes entre 30 et 40 ans, (2) dépourvu de symptômes psychotiques ou de psychoses. Les critères d'exclusion des sujets sont : (1) consommation d'alcool ou de drogues, (2) troubles psycho-organiques, (3) retard mental, (4) difficulté de compréhension de la langue française, (5) état de décompensation aiguë empêchant la réalisation de l'étude. Trois instruments sont utilisés comme supports d'analyses pour cette étude : (1) ELADEB, (2) l'Eye tracking et (3) le Gaze tracker. Le dispositif (2) d'Eye tracking se présente sous forme de lunettes particulières à porter par le sujet et qui permet de suivre les mouvements de l'oeil. L'une des caméras suit et enregistre les mouvements oculaires du sujet et permet de « voir en temps réel ce que voit le sujet et où il regarde » tandis que la seconde caméra scrute et analyse sa pupille. Les données sont ensuite répertoriées par le logiciel de mesures (3) « Gaze tracker », qui les analyse avec, à la fois une évaluation quantitative des points de fixation2 en se basant sur leurs nombres et leurs durées, ainsi qu'une mesure de la variation pupillaire fournie en pixels par le logiciel. Résultat(s) escompté(s) Il s'agit d'une étude exploratoire dans laquelle on espère retrouver les variations moyennes intra-sujets selon les hypothèses carte problème versus non problèmes. On peut s'attendre à trouver une retraduction des mesures de l'échelle ELADEB au travers de l'Eye tracking, ce qui concorderait avec les hypothèses énoncées et ajouterait encore d'avantage de validation à ELADEB au travers d'un outil pointu de mesure physiologique.

Hardcopy quality parameters to ensure structures detection at digital mammography

Objective To develop procedures to ensure consistency of printing quality of digital images, by means of hardcopy quantitative analysis based on a standard image. Materials and Methods Characteristics of mammography DI-ML and general purpose DI-HL films were studied through the QC-Test utilizing different processing techniques in a FujiFilm®-DryPix4000 printer. A software was developed for sensitometric evaluation, generating a digital image including a gray scale and a bar pattern to evaluate contrast and spatial resolution. Results Mammography films showed maximum optical density of 4.11 and general purpose films, 3.22. The digital image was developed with a 33-step wedge scale and a high-contrast bar pattern (1 to 30 lp/cm) for spatial resolution evaluation. Conclusion Mammographic films presented higher values for maximum optical density and contrast resolution as compared with general purpose films. The utilized digital processing technique could only change the image pixels matrix values and did not affect the printing standard. The proposed digital image standard allows greater control of the relationship between pixels values and optical density obtained in the analysis of films quality and printing systems.

Raspberry Pi: a 35-dollar device for viewing DICOM images

Raspberry Pi is a low-cost computer created with educational purposes. It uses Linux and, most of times, freeware applications, particularly a software for viewing DICOM images. With an external monitor, the supported resolution (1920 × 1200 pixels) allows for the set up of simple viewing workstations at a reduced cost.

Microcalcification evaluation in computer assisted diagnosis for digital mammography

In order to develop applications for z;isual interpretation of medical images, the early detection and evaluation of microcalcifications in digital mammograms is verg important since their presence is oftenassociated with a high incidence of breast cancers. Accurate classification into benign and malignant groups would help improve diagnostic sensitivity as well as reduce the number of unnecessa y biopsies. The challenge here is the selection of the useful features to distinguish benign from malignant micro calcifications. Our purpose in this work is to analyse a microcalcification evaluation method based on a set of shapebased features extracted from the digitised mammography. The segmentation of the microcalcificationsis performed using a fixed-tolerance region growing method to extract boundaries of calcifications with manually selected seed pixels. Taking into account that shapes and sizes of clustered microcalcificationshave been associated with a high risk of carcinoma based on digerent subjective measures, such as whether or not the calcifications are irregular, linear, vermiform, branched, rounded or ring like, our efforts were addressed to obtain a feature set related to the shape. The identification of the pammeters concerning the malignant character of the microcalcifications was performed on a set of 146 mammograms with their real diagnosis known in advance from biopsies. This allowed identifying the following shape-based parameters as the relevant ones: Number of clusters, Number of holes, Area, Feret elongation, Roughness, and Elongation. Further experiments on a set of 70 new mammogmms showed that the performance of the classification scheme is close to the mean performance of three expert radiologists, which allows to consider the proposed method for assisting the diagnosis and encourages to continue the investigation in the senseof adding new features not only related to the shape

Active regions for colour texture segmentation integrating region and boundary information

In this paper a colour texture segmentation method, which unifies region and boundary information, is proposed. The algorithm uses a coarse detection of the perceptual (colour and texture) edges of the image to adequately place and initialise a set of active regions. Colour texture of regions is modelled by the conjunction of non-parametric techniques of kernel density estimation (which allow to estimate the colour behaviour) and classical co-occurrence matrix based texture features. Therefore, region information is defined and accurate boundary information can be extracted to guide the segmentation process. Regions concurrently compete for the image pixels in order to segment the whole image taking both information sources into account. Furthermore, experimental results are shown which prove the performance of the proposed method

Unsupervised active regions for multiresolution image segmentation

An unsupervised approach to image segmentation which fuses region and boundary information is presented. The proposed approach takes advantage of the combined use of 3 different strategies: the guidance of seed placement, the control of decision criterion, and the boundary refinement. The new algorithm uses the boundary information to initialize a set of active regions which compete for the pixels in order to segment the whole image. The method is implemented on a multiresolution representation which ensures noise robustness as well as computation efficiency. The accuracy of the segmentation results has been proven through an objective comparative evaluation of the method

A concurrent region growing algorithm guided by circumscribed contours

Image segmentation of natural scenes constitutes a major problem in machine vision. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. This approach begins by detecting the main contours of the scene which are later used to guide a concurrent set of growing processes. A previous analysis of the seed pixels permits adjustment of the homogeneity criterion to the region's characteristics during the growing process. Since the high variability of regions representing outdoor scenes makes the classical homogeneity criteria useless, a new homogeneity criterion based on clustering analysis and convex hull construction is proposed. Experimental results have proven the reliability of the proposed approach

Statistical Inversion Theory in X-ray Tomography

In this thesis the X-ray tomography is discussed from the Bayesian statistical viewpoint. The unknown parameters are assumed random variables and as opposite to traditional methods the solution is obtained as a large sample of the distribution of all possible solutions. As an introduction to tomography an inversion formula for Radon transform is presented on a plane. The vastly used filtered backprojection algorithm is derived. The traditional regularization methods are presented sufficiently to ground the Bayesian approach. The measurements are foton counts at the detector pixels. Thus the assumption of a Poisson distributed measurement error is justified. Often the error is assumed Gaussian, altough the electronic noise caused by the measurement device can change the error structure. The assumption of Gaussian measurement error is discussed. In the thesis the use of different prior distributions in X-ray tomography is discussed. Especially in severely ill-posed problems the use of a suitable prior is the main part of the whole solution process. In the empirical part the presented prior distributions are tested using simulated measurements. The effect of different prior distributions produce are shown in the empirical part of the thesis. The use of prior is shown obligatory in case of severely ill-posed problem.

LSB Matching Steganalysis Based on Patterns of Pixel Differences and Random Embedding

Peer-reviewed

Desenvolvimento de um algoritmo para identificação e correção de spikes em espectroscopia Raman de imagem

Raman imaging spectroscopy is a highly useful analytical tool that provides spatial and spectral information on a sample. However, CCD detectors used in dispersive instruments present the drawback of being sensitive to cosmic rays, giving rise to spikes in Raman spectra. Spikes influence variance structures and must be removed prior to the use of multivariate techniques. A new algorithm for correction of spikes in Raman imaging was developed using an approach based on comparison of nearest neighbor pixels. The algorithm showed characteristics including simplicity, rapidity, selectivity and high quality in spike removal from hyperspectral images.

Desenhos de estruturas químicas correlacionam-se com propriedades biológicas: MIA-QSAR

Descriptors in multivariate image analysis applied to quantitative structure-activity relationship (MIA-QSAR) are pixels of bidimensional images of chemical structures (drawings), which were used to model the trichomonicidal activities of a series of benzimidazole derivatives. The MIA-QSAR model showed good predictive ability, with r², q² and r val. ext.² of 0.853, 0.519 and 0.778, respectively, which are comparable to the best values obtained by CoMFA e CoMSIA for the same series. A MIA-based analysis was also performed by using images of alphabetic letters with the corresponding numeric ordering as dependent variables, but no correlation was found, supporting that MIA-QSAR is not arbitrary.

Exploring potentialities of the HR-CS FAAS technique in the determination of Ni and Pb in mineral waters

National Health Surveillance Agency (ANVISA) established in the decree number 54 maximum allowed levels for Ni and Pb in mineral and natural waters at 20 µg L-1 and 10 µg L-1, respectively. For screening analysis purposes, the high-resolution continuum source flame atomic absorption spectrometry technique (HR-CS FAAS) was evaluated for the fast-sequential determination of nickel and lead in mineral waters.Two atomic lines for Ni (232.003 nm - main and 341.477 nm - secondary) and Pb (217.0005 nm - main and 283.306 nm - secondary) at different wavelength integrated absorbance (number of pixels) were evaluated. Sensitivity enhanced with the increase of the number of pixels and with the summation of the atomic lines absorbances. The main figures of merit associated to the HR-CS FAAS technique were compared with that obtained by line-source flame atomic absorption spectrometry (LS FAAS). Water samples were pre-concentrated about 5-fold by evaporation before analysis. Recoveries of Pb significantly varied with increased wavelength integrated absorbance. Better recoveries (92-93%) were observed for higher number of pixels at the main line or summating the atomic lines (90-92%). This influence was irrelevant for Ni, and recoveries in the 92-104% range were obtained in all situations.

Spatial and Spectral Separability of Grasslands in the inner Turku Archipelago using Landsat Thematic Mapper Satellite Imagery

The present study investigates the spatial and spectral discrimination potential for grassland patches in the inner Turku Archipelago using Landsat Thematic Mapper satellite imagery. The spatial discrimination potential was computed through overlay analysis using official grassland parcel data and a hypothetical 30 m resolution satellite image capturing the site. It found that Landsat TM imagery’s ability to retrieve pure or near-pure pixels (90% purity or more) from grassland patches smaller than 1 hectare was limited to 13% success, compared to 52% success when upscaling the resolution to 10 x 10 m pixel size. Additionally, the perimeter/area patch metric is proposed as a predictor for the suitability of the spatial resolution of input imagery. Regression analysis showed that there is a strong negative correlation between a patch’s perimeter/area ratio and its pure pixel potential. The study goes on to characterise the spectral response and discrimination potential for the five main grassland types occurring in the study area: recreational grassland, traditional pasture, modern pasture, fodder production grassland and overgrown grassland. This was done through the construction of spectral response curves, a coincident spectral plot and a contingency matrix as well as by calculating the transformed divergence for the spectral signatures, all based on training samples from the TM imagery. Substantial differences in spectral discrimination potential between imagery from the beginning of the growing season and the middle of summer were found. This is because the spectral responses for these five grassland types converge as the peak of the growing season draws nearer. Recreational grassland shows a consistent discrimination advantage over other grassland types, whereas modern pasture is most easily confused. Traditional pasture land, perhaps the most biologically valuable grassland type, can be spectrally discriminated from other grassland types with satisfactory success rates provided early growing season imagery is used.

Mathematical equation correction to spectral and transport interferences in high-resolution continuum source flame atomic absorption spectrometry: determination of lead in phosphoric acid

In this work, a new mathematical equation correction approach for overcoming spectral and transport interferences was proposed. The proposal was applied to eliminate spectral interference caused by PO molecules at the 217.0005 nm Pb line, and the transport interference caused by variations in phosphoric acid concentrations. Correction may be necessary at 217.0005 nm to account for the contribution of PO, since Atotal217.0005 nm = A Pb217.0005 nm + A PO217.0005 nm. This may be easily done by measuring other PO wavelengths (e.g. 217.0458 nm) and calculating the relative contribution of PO absorbance (A PO) to the total absorbance (Atotal) at 217.0005 nm: A Pb217.0005 nm = Atotal217.0005 nm - A PO217.0005 nm = Atotal217.0005 nm - k (A PO217.0458 nm). The correction factor k is calculated from slopes of calibration curves built up for phosphorous (P) standard solutions measured at 217.0005 and 217.0458 nm, i.e. k = (slope217.0005 nm/slope217.0458 nm). For wavelength integrated absorbance of 3 pixels, sample aspiration rate of 5.0 ml min-1, analytical curves in the 0.1 - 1.0 mg L-1 Pb range with linearity better than 0.9990 were consistently obtained. Calibration curves for P at 217.0005 and 217.0458 nm with linearity better than 0.998 were obtained. Relative standard deviations (RSD) of measurements (n = 12) in the range of 1.4 - 4.3% and 2.0 - 6.0% without and with mathematical equation correction approach were obtained respectively. The limit of detection calculated to analytical line at 217.0005 nm was 10 µg L-1 Pb. Recoveries for Pb spikes were in the 97.5 - 100% and 105 - 230% intervals with and without mathematical equation correction approach, respectively.

Análise discriminante paramétrica para reconhecimento de defeitos em tábuas de eucalipto utilizando imagens digitais

A indústria de madeira tem dispensado especial atenção às etapas de classificação e seleção de madeira serrada. Sistemas de Visão Artificial têm sido propostos para automação dessas etapas na indústria. A identificação de características apropriadas para discriminar os defeitos da madeira em imagens digitais é um dos maiores desafios no desenvolvimento desta tecnologia. O objetivo deste trabalho foi avaliar, por meio de técnicas de análise multivariada, a capacidade de discriminar defeitos em tábuas de eucalipto, utilizando-se as características de percentis de imagens coloridas. Foram realizadas análises discriminantes linear e quadrática para classificação de defeitos e madeira limpa em imagens digitais de tábuas de eucaliptos. As características de percentis do histograma das bandas do vermelho, verde e azul, retiradas de dois tamanhos de blocos de imagens, foram utilizadas para desenvolvimento e teste das funções discriminantes. Foram usados 492 blocos, contendo os 12 defeitos estudados e madeira limpa, retirados das imagens de 40 tábuas amostradas aleatoriamente. As características foram analisadas com seus valores originais, escores dos componentes principais e escores das variáveis canônicas. Os menores erros globais de classificação foram 19 e 24% para funções discriminantes lineares com os escores das variáveis canônicas para tamanho de bloco de 64 x 64 e 32 x 32 pixels, respectivamente. Tendo em vista a magnitude desses erros, as características de percentis foram consideradas adequadas para discriminar defeitos e madeira limpa em imagens digitais.