A competitive scheme for storing sparse representation of X-Ray medical images

A competitive scheme for economic storage of the informational content of an X-Ray image, as it can be used for further processing, is presented. It is demonstrated that sparse representation of that type of data can be encapsulated in a small file without affecting the quality of the recovered image. The proposed representation, which is inscribed within the context of data reduction, provides a format for saving the image information in a way that could assist methodologies for analysis and classification. The competitiveness of the resulting file is compared against the compression standards JPEG and JPEG200

Automatic detection of solitary pulmonary nodules using swarm intelligence optimized neural networks on CT images

Lung Cancer is one of the most dangerous diseases that cause a large number of deaths. Early detection and analysis will be the only remedy. Computer-Aided Diagnosis (CAD) plays a key role in the early detection and diagnosis of lung cancer. This paper develops a CAD system that focus on new heuristic search algorithm to optimize the Back Propagation Neural Network (BPNN) in characterizing nodule from non-nodules. The proposed CAD system consists of four main stages: (i) image acquisition (ii) lesion detection, (iii) texture feature extraction and (iv) tumor characterization using a classifier. The optimization mechanism employs Particle Swarm Optimization (PSO) with new inertia weight for NN in order to investigate the classification rate of these algorithms in reducing the problems of trapping in local minima and the slow convergence rate of current evolutionary learning algorithms. The experiments were conducted on CT images to classify into nodule and non-nodule from the tumor region of interest. The performance of the CAD system was evaluated for the texture characterized images taken from LIDC-IDRI and SPIE-AAPM databases. Due to improved inertia weight used in Particle Swarm (PS) the CAD achieves highest classification accuracy of 98% for solid nodules, 99.5% for part solid nodules and 97.2% for non solid nodules respectively. The experimental results suggest that the developed CAD system has great potential and promise in the automatic diagnosis of tumors of lung

Segmentation of lung nodule in CT data using active contour model and Fuzzy C-mean clustering

AbstractThe aim of this paper was to develop a region based active contour model and Fuzzy C-Means (FCM) technique for segmentation of lung nodules. Ultimately, detection and assisted diagnosis of nodules at earlier stage increase the mortality rate. Among many imaging modalities, Computed Tomography (CT) is being the most sought because of its imaging sensitivity, high resolution and isotropic acquisition in locating the lung lesions. The proposed methodology focuses on acquisition of CT images, reconstruction of lung parenchyma and segmentation of lung nodules. Reconstruction of parenchyma can be employed using selective binary and Gaussian filtering with new signed pressure force function (SBGF-new SPF) and clustering technique was used for nodule segmentation. Comparative experiments demonstrate the advantages of the proposed method in terms of decreased error rate and increased similarity measure

Banco Mundial de Datos sobre Salud Bucodental de la OMS, 1986-1996: panorámica de las encuestas de salud bucodental a los 12 años de edad

En el presente artículo se describe la situación mundial de la salud bucodental de los niños de 12 años de edad -el índice de dientes cariados, perdidos y obturados (CPO) y el porcentaje de la población afectada- a partir de los estudios representativos más recientes sobre 80 países incluidos en el Banco Mundial de Datos sobre Salud Bucodental (BMDSB) de la OMS entre 1986 y 1996. El volumen de información varió mucho: 68% de las economías de mercado de los países desarrollados tenían por lo menos un conjunto nacional de datos, en comparación con 38% de las economías de los países en desarrollo y 36% de las economías en transición. Las proporciones en cada Región de la OMS fueron las siguientes: Mediterráneo Oriental, 55%; Europa, 50%; Pacífico Occidental, 48%; África, 39%; Asia Sudoriental, 30%; y las Américas, 26%. En el mundo en general, el índice ponderado de dientes CPO en todos los datos del BMDSB es <3,0%, que es la meta de la OMS/Federación Dental Internacional para el año 2000. Con respecto a los datos reseñados en el presente artículo, se discuten el logro y el incumplimiento de esa meta, al igual que la variación del índice medio de dientes CPO y la proporción de niños afectados en varias agrupaciones de países. Hay dificultades para obtener datos recientes sobre muchos países, pero en el artículo se recalca la necesidad de mantener y ampliar el BMDSB para facilitar la recopilación de datos de salud bucodental válidos, fidedignos y comparables