Diseño e implementación de un módulo para la anotación de imágenes médicas

Se comenzó el trabajo recabando información sobre los distintos enfoques que se le había dado a la anotación a lo largo del tiempo, desde anotación de imágenes a mano, pasando por anotación de imágenes utilizando características de bajo nivel, como color y textura, hasta la anotación automática. Tras entrar en materia, se procedió a estudiar artículos relativos a los diferentes algoritmos utilizados para la anotación automática de imágenes. Dado que la anotación automática es un campo bastante abierto, hay un gran numero de enfoques. Teniendo las características de las imágenes en particular en las que se iba a centrar el proyecto, se fueron descartando los poco idoneos, bien por un coste computacional elevado, o porque estaba centrado en un tipo diferente de imágenes, entre otras cosas. Finalmente, se encontró un algoritmo basado en formas (Active Shape Model) que se consideró que podría funcionar adecuadamente. Básicamente, los diferentes objetos de la imagen son identicados a partir de un contorno base generado a partir de imágenes de muestra, siendo modicado automáticamente para cubrir la zona deseada. Dado que las imágenes usadas son todas muy similares en composición, se cree que puede funcionar bien. Se partió de una implementación del algoritmo programada en MATLAB. Para empezar, se obtuvieron una serie de radiografías del tórax ya anotadas. Las imágenes contenían datos de contorno para ambos pulmones, las dos clavículas y el corazón. El primer paso fue la creación de una serie de scripts en MATLAB que permitieran: - Leer y transformar las imágenes recibidas en RAW, para adaptarlas al tamaño y la posición de los contornos anotados - Leer los archivos de texto con los datos de los puntos del contorno y transformarlos en variables de MATLAB - Unir la imagen transformada con los puntos y guardarla en un formato que la implementación del algoritmo entendiera. Tras conseguir los ficheros necesarios, se procedió a crear un modelo para cada órgano utilizando para el entrenamiento una pequeña parte de las imágenes. El modelo obtenido se probó con varias imágenes de las restantes. Sin embargo, se encontro bastante variación dependiendo de la imagen utilizada y el órgano detectado. ---ABSTRACT---The project was started by procuring information about the diferent approaches to image annotation over time, from manual image anotation to automatic annotation. The next step was to study several articles about the diferent algorithms used for automatic image annotation. Given that automatic annotation is an open field, there is a great number of approaches. Taking into account the features of the images that would be used, the less suitable algorithms were rejected. Eventually, a shape-based algorithm (Active Shape Model) was found. Basically, the diferent objects in the image are identified from a base contour, which is generated from training images. Then this contour is automatically modified to cover the desired area. Given that all the images that would be used are similar in object placement, the algorithm would probably work nicely. The work started from a MATLAB implementation of the algorithm. To begin with, a set of chest radiographs already annotated were obtained. These images came with contour data for both lungs, both clavicles and the heart. The first step was the creation of a series of MATLAB scripts to join the RAW images with the annotation data and transform them into a format that the algorithm could read. After obtaining the necessary files, a model for each organ was created using part of the images for training. The trained model was tested on several of the reimaining images. However, there was much variation in the results from one image to another. Generally, lungs were detected pretty accurately, whereas clavicles and the heart gave more problems. To improve the method, a new model was trained using half of the available images. With this model, a significant inprovement of the results can be seen.

Redesign of soluble fatty acid desaturases from plants for altered substrate specificity and double bond position

Acyl-acyl carrier protein (ACP) desaturases introduce double bonds at specific positions in fatty acids of defined chain lengths and are one of the major determinants of the monounsaturated fatty acid composition of vegetable oils. Mutagenesis studies were conducted to determine the structural basis for the substrate and double bond positional specificities displayed by acyl-ACP desaturases. By replacement of specific amino acid residues in a Δ6-palmitoyl (16:0)-ACP desaturase with their equivalents from a Δ9-stearoyl (18:0)-ACP desaturase, mutant enzymes were identified that have altered fatty acid chain-length specificities or that can insert double bonds into either the Δ6 or Δ9 positions of 16:0- and 18:0-ACP. Most notably, by replacement of five amino acids (A181T/A200F/S205N/L206T/G207A), the Δ6-16:0-ACP desaturase was converted into an enzyme that functions principally as a Δ9-18:0-ACP desaturase. Many of the determinants of fatty acid chain-length specificity in these mutants are found in residues that line the substrate binding channel as revealed by x-ray crystallography of the Δ9-18:0-ACP desaturase. The crystallographic model of the active site is also consistent with the diverged activities associated with naturally occurring variant acyl-ACP desaturases. In addition, on the basis of the active-site model, a Δ9-18:0-ACP desaturase was converted into an enzyme with substrate preference for 16:0-ACP by replacement of two residues (L118F/P179I). These results demonstrate the ability to rationally modify acyl-ACP desaturase activities through site-directed mutagenesis and represent a first step toward the design of acyl-ACP desaturases for the production of novel monounsaturated fatty acids in transgenic oilseed crops.

Mathematical approach for predicting non-negative tristimulus values using the CAT02 chromatic adaptation transform

It has been reported that for certain colour samples, the chromatic adaptation transform CAT02 imbedded in the CIECAM02 colour appearance model predicts corresponding colours with negative tristimulus values (TSVs), which can cause problems in certain applications. To overcome this problem, a mathematical approach is proposed for modifying CAT02. This approach combines a non-negativity constraint for the TSVs of corresponding colours with the minimization of the colour differences between those values for the corresponding colours obtained by visual observations and the TSVs of the corresponding colours predicted by the model, which is a constrained non-linear optimization problem. By solving the non-linear optimization problem, a new matrix is found. The performance of the CAT02 transform with various matrices including the original CAT02 matrix, and the new matrix are tested using visual datasets and the optimum colours. Test results show that the CAT02 with the new matrix predicted corresponding colours without negative TSVs for all optimum colours and the colour matching functions of the two CIE standard observers under the test illuminants considered. However, the accuracy with the new matrix for predicting the visual data is approximately 1 CIELAB colour difference unit worse compared with the original CAT02. This indicates that accuracy has to be sacrificed to achieve the non-negativity constraint for the TSVs of the corresponding colours.

Measuring color differences in gonioapparent materials used in the automotive industry

This paper illustrates how to design a visual experiment to measure color differences in gonioapparent materials and how to assess the merits of different advanced color-difference formulas trying to predict the results of such experiment. Successful color-difference formulas are necessary for industrial quality control and artificial color-vision applications. A color- difference formula must be accurate under a wide variety of experimental conditions including the use of challenging materials like, for example, gonioapparent samples. Improving the experimental design in a previous paper [Melgosaet al., Optics Express 22, 3458-3467 (2014)], we have tested 11 advanced color-difference formulas from visual assessments performed by a panel of 11 observers with normal colorvision using a set of 56 nearly achromatic colorpairs of automotive gonioapparent samples. Best predictions of our experimental results were found for the AUDI2000 color-difference formula, followed by color-difference formulas based on the color appearance model CIECAM02. Parameters in the original weighting function for lightness in the AUDI2000 formula were optimized obtaining small improvements. However, a power function from results provided by the AUDI2000 formula considerably improved results, producing values close to the inter-observer variability in our visual experiment. Additional research is required to obtain a modified AUDI2000 color-difference formula significantly better than the current one.

μ-MAR: Multiplane 3D Marker based Registration for depth-sensing cameras

Many applications including object reconstruction, robot guidance, and. scene mapping require the registration of multiple views from a scene to generate a complete geometric and appearance model of it. In real situations, transformations between views are unknown and it is necessary to apply expert inference to estimate them. In the last few years, the emergence of low-cost depth-sensing cameras has strengthened the research on this topic, motivating a plethora of new applications. Although they have enough resolution and accuracy for many applications, some situations may not be solved with general state-of-the-art registration methods due to the signal-to-noise ratio (SNR) and the resolution of the data provided. The problem of working with low SNR data, in general terms, may appear in any 3D system, then it is necessary to propose novel solutions in this aspect. In this paper, we propose a method, μ-MAR, able to both coarse and fine register sets of 3D points provided by low-cost depth-sensing cameras, despite it is not restricted to these sensors, into a common coordinate system. The method is able to overcome the noisy data problem by means of using a model-based solution of multiplane registration. Specifically, it iteratively registers 3D markers composed by multiple planes extracted from points of multiple views of the scene. As the markers and the object of interest are static in the scenario, the transformations obtained for the markers are applied to the object in order to reconstruct it. Experiments have been performed using synthetic and real data. The synthetic data allows a qualitative and quantitative evaluation by means of visual inspection and Hausdorff distance respectively. The real data experiments show the performance of the proposal using data acquired by a Primesense Carmine RGB-D sensor. The method has been compared to several state-of-the-art methods. The results show the good performance of the μ-MAR to register objects with high accuracy in presence of noisy data outperforming the existing methods.

The use of unwrapped phase in MR image segmentation: A preliminary study

This paper considers the problem of tissue classification in 3D MRI. More specifically, a new set of texture features, based on phase information, is used to perform the segmentation of the bones of the knee. The phase information provides a very good discrimination between the bone and the surrounding tissues, but is usually not used due to phase unwrapping problems. We present a method to extract textural information from the phase that does not require phase unwrapping. The textural information extracted from the magnitude and the phase can be combined to perform tissue classification, and used to initialise an active shape model, leading to a more precise segmentation.

Ambulance Treatment Space Ergonomic Layout

This is the first time a multidisciplinary team has employed an iterative co-design method to determine the ergonomic layout of an emergency ambulance treatment space. This process allowed the research team to understand how treatment protocols were performed and developed analytical tools to reach an optimum configuration towards ambulance design standardisation. Fusari conducted participatory observations during 12-hour shifts with front-line ambulance clinicians, hospital staff and patients to understand the details of their working environments whilst on response to urgent and emergency calls. A simple yet accurate 1:1 mock-up of the existing ambulance was built for detailed analysis of these procedures through simulations. Paramedics were called in to participate in interviews and role-playing inside the model to recreate tasks, how they are performed, the equipment used and to understand the limitations of the current ambulance. The use of Link Analysis distilled 5 modes of use. In parallel, an exhaustive audit of all equipment and consumables used in ambulances was performed (logging and photography) to define space use. These developed 12 layout options for refinement and CAD modelling and presented back to paramedics. The preferred options and features were then developed into a full size test rig and appearance model. Two key studies informed the process. The 2005 National Patient Safety Agency funded study “Future Ambulances” outlined 9 design challenges for future standardisation of emergency vehicles and equipment. Secondly, the 2007 EPSRC funded “Smart Pods” project investigated a new system of mobile urgent and emergency medicine to treat patients in the community. A full-size mobile demonstrator unit featuring the evidence-based ergonomic layout was built for clinical tests through simulated emergency scenarios. Results from clinical trials clearly show that the new layout improves infection control, speeds up treatment, and makes it easier for ambulance crews to follow correct clinical protocols.

Tail gas catalyzed N2O decomposition over Fe-beta zeolite. On the promoting role of framework connected AlO6 sites in the vicinity of Fe by controlled dealumination during exchange

A novel route to prepare highly active and stable N2O decomposition catalysts is presented, based on Fe-exchanged beta zeolite. The procedure consists of liquid phase Fe(III) exchange at low pH. By varying the pH systematically from 3.5 to 0, using nitric acid during each Fe(III)-exchange procedure, the degree of dealumination was controlled, verified by ICP and NMR. Dealumination changes the presence of neighbouring octahedral Al sites of the Fe sites, improving the performance for this reaction. The so-obtained catalysts exhibit a remarkable enhancement in activity, for an optimal pH of 1. Further optimization by increasing the Fe content is possible. The optimal formulation showed good conversion levels, comparable to a benchmark Fe-ferrierite catalyst. The catalyst stability under tail gas conditions containing NO, O2 and H2O was excellent, without any appreciable activity decay during 70 h time on stream. Based on characterisation and data analysis from ICP, single pulse excitation NMR, MQ MAS NMR, N2 physisorption, TPR(H2) analysis and apparent activation energies, the improved catalytic performance is attributed to an increased concentration of active sites. Temperature programmed reduction experiments reveal significant changes in the Fe(III) reducibility pattern with the presence of two reduction peaks; tentatively attributed to the interaction of the Fe-oxo species with electron withdrawing extraframework AlO6 species, causing a delayed reduction. A low-temperature peak is attributed to Fe-species exchanged on zeolitic AlO4 sites, which are partially charged by the presence of the neighbouring extraframework AlO6 sites. Improved mass transport phenomena due to acid leaching is ruled out. The increased activity is rationalized by an active site model, whose concentration increases by selectively washing out the distorted extraframework AlO6 species under acidic (optimal) conditions, liberating active Fe species.

Identificação dos principais fatores determinantes do envelhecimento ativo na população idosa do distrito de Castelo Branco - Portugal

Tese de Doutoramento em Gerontologia apresentada à Universidade de Extremadura, Espanha

Synthesis of homoallylic oxygenated alpha-methylene-gamma-butyrolactones: a model for preparing biologically active natural lactones

In this Letter we describe a 12% overall yield synthesis of a model for homoallylic oxygenated alpha-methylene-gamma-butyrolactones with relative stereochemistry defined by selective hydrogenation with Rh/Al(2)O(3). The synthesis was realized in 9 steps involving simple reactions. (C) 2008 Elsevier Ltd. All rights reserved.

Active shape structural model

Shape model, deformable models, structural models, biometry, content based image retrieval, sketches

Subjective health assessments and active labor market participation of older men: evidence from a semiparametric binary choice model with nonadditive correlated individual-specific effects

We use panel data from the U. S. Health and Retirement Study, 1992-2002, to estimate the effect of self-assessed health limitations on the active labor market participation of older men. Self-assessments of health are likely to be endogenous to labor supply due to justification bias and individual-specific heterogeneity in subjective evaluations. We address both concerns. We propose a semiparametric binary choice procedure that incorporates nonadditive correlated individual-specific effects. Our estimation strategy identifies and estimates the average partial effects of health and functioning on labor market participation. The results indicate that poor health plays a major role in labor market exit decisions.

A clinical prognostic model for the identification of low-risk patients with acute symptomatic pulmonary embolism and active cancer.

BACKGROUND: Physicians need a specific risk-stratification tool to facilitate safe and cost-effective approaches to the management of patients with cancer and acute pulmonary embolism (PE). The objective of this study was to develop a simple risk score for predicting 30-day mortality in patients with PE and cancer by using measures readily obtained at the time of PE diagnosis. METHODS: Investigators randomly allocated 1,556 consecutive patients with cancer and acute PE from the international multicenter Registro Informatizado de la Enfermedad TromboEmbólica to derivation (67%) and internal validation (33%) samples. The external validation cohort for this study consisted of 261 patients with cancer and acute PE. Investigators compared 30-day all-cause mortality and nonfatal adverse medical outcomes across the derivation and two validation samples. RESULTS: In the derivation sample, multivariable analyses produced the risk score, which contained six variables: age > 80 years, heart rate ≥ 110/min, systolic BP < 100 mm Hg, body weight < 60 kg, recent immobility, and presence of metastases. In the internal validation cohort (n = 508), the 22.2% of patients (113 of 508) classified as low risk by the prognostic model had a 30-day mortality of 4.4% (95% CI, 0.6%-8.2%) compared with 29.9% (95% CI, 25.4%-34.4%) in the high-risk group. In the external validation cohort, the 18% of patients (47 of 261) classified as low risk by the prognostic model had a 30-day mortality of 0%, compared with 19.6% (95% CI, 14.3%-25.0%) in the high-risk group. CONCLUSIONS: The developed clinical prediction rule accurately identifies low-risk patients with cancer and acute PE.