A DSP-BASED active contour model

In this paper a DSP-based active contour model for tracking of the endocardium in a sequence of echocardiographic images is presented. If a contour is available in the first frame of a sequence, the contours in the subsequent frames are segmented. Deformable active contours is a technique that combine geometry, physics and approximation theory in order to solve problems of fundamental importance to medical image analysis; such as segmentation, representation and matching of shapes, and the tracking of objects in movement. The procedure has been developed on a DSP processor using its hardware features. The results are illustrated using a sequence of four-chambers apical echocardiographic images

Reduction of the speckle noise in echocardiographic images by a cubic spline filter

One of the main problems to resolve in the processing of biomedical images is the reduction of noise. The problem is specially important if the noise has a multiplicative nature (speckle noise), for instance if the object of analysis is an ultrasonic image. In this report we carry out a review of techniques which can be used to reduce this type of noise on four-chamber view B-mode echocardiographic images in an appropriated way. Different ways of nonlinear filtering, adaptive techniques based on the statistical ordering and a cubic spline interpolation will be shown as suitable techniques for this objective but regarding quantitative and qualitative results we have obtained, we can confirm that a cubic spline filter is the most suitable filter that we have reviewed.This work has been supported by Fundación Séneca of Región de Murcia and Ministerio de Ciencia y Tecnología of Spain, under grants PB/63/FS/02 and TIC2003-09400- C04-02, respectively

An automatic welding defects classifier system

Radiographic inspection is a well-established testing method to detect weld defects. However, interpretation of radiographic films is a difficult task. The reliability of such interpretation and the expense of training suitable experts have allowed that the efforts being made towards automation in this field. In this paper, we describe an automatic detection system to recognise welding defects in radiographic images. In a first stage, image processing techniques, including noise reduction, contrast enhancement, thresholding and labelling were implemented to help in the recognition of weld regions and the detection of weld defects. In a second stage, a set of geometrical features was proposed and extracted between defect candidates. In a third stage, an artificial neural network for weld defect classification was used under three regularisation process with different architectures. For the input layer, the principal component analysis technique was used in order to reduce the number of feature variables; and, for the hidden layer, a different number of neurons was used in the aim to give better performance for defect classification in both cases

Implementación de sistemas fuzzy complejos sobre FPGAs

Las desventajas de las soluciones hardware dedicadas para la implementación de sistemas de inferencia fuzzy cuando se comparan con las estrategias basadas en software son principalmente la falta de flexibilidad y la complicación en el proceso de diseño. En este trabajo se presenta una arquitectura novedosa que permite la síntesis electrónica y la implementación hardware de sistemas expertos basados en conocimiento fuzzy. La definición de la arquitectura se basa en la descripción en forma de red de Petri de la base de reglas complejas, heredando de ella las características de modularidad y escalabilidad. Los componentes de nuestra arquitectura se definen entonces utilizando descripciones VHDL de alto nivel. Por ello, nuestra metodología de diseño proporciona flexibilidad, reusabilidad e independencia tanto de la tecnología electrónica como del tipo y tamaño de la aplicación, solucionando la mayoría de las limitaciones del hardware fuzzy

Comparative analysis of two operational amplifier topologies for a 40MS/s 12-bit pipelined ADC in 0.35μm CMOS

This paper describes a comparative analysis between two topologies of operational amplifiers to design a 40 MS/s 12-bit pipeline analog to digital converter (ADC). The analysis includes AC and transient simulation to select the proper topology. This ADC is implemented in a 0.35 mum AMS CMOS technology with 3.3 V single power supply. The capacitors and selected operational amplifiers were scaled for low power dissipation. All analog components of this pipeline ADC are fully differential, as there are dynamic comparators, analog multiplexers and operational amplifiers with gain boosting.This work has been partially supported by Fundación Séneca of Región de Murcia(Ref:03094/PI/05)and MEC of Spain(Ref:TIN2006-15460-C04-04)

Efficient method for events detection in phonocardiographic signals

The auscultation of the heart is still the first basic analysis tool used to evaluate the functional state of the heart, as well as the first indicator used to submit the patient to a cardiologist. In order to improve the diagnosis capabilities of auscultation, signal processing algorithms are currently being developed to assist the physician at primary care centers for adult and pediatric population. A basic task for the diagnosis from the phonocardiogram is to detect the events (main and additional sounds, murmurs and clicks) present in the cardiac cycle. This is usually made by applying a threshold and detecting the events that are bigger than the threshold. However, this method usually does not allow the detection of the main sounds when additional sounds and murmurs exist, or it may join several events into a unique one. In this paper we present a reliable method to detect the events present in the phonocardiogram, even in the presence of heart murmurs or additional sounds. The method detects relative maxima peaks in the amplitude envelope of the phonocardiogram, and computes a set of parameters associated with each event. Finally, a set of characteristics is extracted from each event to aid in the identification of the events. Besides, the morphology of the murmurs is also detected, which aids in the differentiation of different diseases that can occur in the same temporal localization. The algorithms have been applied to real normal heart sounds and murmurs, achieving satisfactory results.This work has been supported by Fundación Séneca of Región de Murcia and Ministerio de Ciencia y Tecnología of Spain, under grants PB/63/FS/02 and TIC2003-09400-C04-02, respectively

Power reduction of a 12-bit 40-MS/s pipeline ADC exploiting partial amplifier sharing

High performance analog-to-digital converters (ADC) are essential elements for the development of high performance image sensors. These circuits need a big number of ADCs to reach the required resolution at a specified speed. Moreover, nowadays power dissipation has become a key performance to be considered in analog designs, specially in those developed for portable devices. Design of such circuits is a challenging task which requires a combination of the most advanced digital circuit, the analog expertise knowledge and an iterative design. Amplifier sharing has been a commonly used technique to reduce power dissipation in pipelined ADCs. In this paper we present a partial amplifier sharing topology of a 12 bit pipeline ADC, developed in 0.35 mum CMOS process. Its performance is compared with a conventional amplifier scaling topology and with a fully amplifier sharing one.This work has been supported by Ministerio de Educación y Ciencia of Spain and the European Regional Development Fund of the European Commission (FEDER) under grant TIN2006-15460-C04-04

Using deep learning for defect classification on a small weld X-ray image dataset

This document provides a comparative evaluation of the performance of a deep learning network for different combinations of parameters and hyper-parameters. Although there are numerous studies that report on performance in deep learning networks for ordinary data sets, their performance on small data sets is much less evaluated. The objective of this work is to demonstrate that such a challenging small data set, such as a welding X-ray image data set, can be trained and evaluated obtaining high precision and that it is possible thanks to data augmentation. In fact, this article shows that data augmentation, also a typical technique in any learning process on a large data set, plus that two image channels, such as channels B (blue) and G (green), both are replaced by the Canny edge map and a binary image provided by an adaptive Gaussian threshold, respectively, gives to the network a 3% increase in accuracy, approximately. In summary, the objective of this work is to present the methodology used and the results obtained to estimate the classification accuracy of three main classes of welding defects obtained on a small set of welding X-ray image data.The authors wants to acknowledge the work of the rest of the participants in this project, namely: J.A. López-Alcantud, P. Rubio-Ibañez, Universidad Politécnica de Cartagena, J.A. Díaz-Madrid, Centro Universitario de la Defensa - UPCT and T.J. Kazmierski, University of Southampton. This work has been partially funded by Spanish government through project numbered RTI2018-097088-B-C33 (MINECO/FEDER,UE)

Controlador fuzzy de dos etapas para frenos ABS

[ESP] En este artículo se presenta un nuevo controlador fuzzy jerárquico de dos etapas para sistemas ABS. En una primera etapa el controlador estima el deslizamiento que ha de tener la rueda del vehículo para conseguir la mejor frenada posible en función del tipo de firme y en una segunda calcula cual debe ser el par de frenado más adecuado para cada instante. [ENG]In this article a new two-stages hierarchical fuzzy controller for Anti-lock Braking Systems is presented. In the first stage, the controller estimates the optimum slip ratio between tire and driving surface to obtain the highest friction based on the type of pavement. In the second stage it calculates the braking torque to apply at every instant

Perfil del paciente canino con cuerpos extraños esofágicos

Objetivo. Determinar el perfil del paciente canino que presenta cuerpos extraños esofágicos para identificar las características de riesgo al presentar esta entidad. Materiales y métodos. Este es un estudio retrospectivo realizado en el Hospital Clínico Veterinario de la Universidad de Extremadura (HCV). Se analizaron diferentes parámetros de los perros que presentaron un diagnóstico endoscópico de cuerpos extraños esofágicos. Resultados. Esta patología se presentó más comúnmente en perros adultos jóvenes y en pacientes de raza pequeña. Se presenta por primera vez al Podenco Portugués, el cual además representó la raza con mayor factor de riesgo. Conclusiones. Los resultados obtenidos en esta investigación concuerdan con lo descrito anteriormente en cuanto a las características del paciente con cuerpo extraño esofágico. Asimismo, se reporta el Podenco Portugués como predispuesto a esta entidad, con un factor de riesgo mayor al de otras razas anteriormente mencionadas en la literatura. Para prevenir los cuerpos extraños esofágicos, se debe alimentar con carne cruda y huesos a los perros, especialmente a los de raza pequeña. Siempre se debe tener en cuenta esta patología en los perros con sintomatología de enfermedad esofágica sin importar su edad, pues su presentación es más común en perros adultos jóvenes.Objective. Determine the profile of the canine patient with esophageal foreign bodies to identify risk factors associated with the foreign bodies. Materials and Methods. This is a retrospective study made by the Veterinary Hospital Clinic of the Universidad de Extremadura (VHC). Different factors were analyzed in dogs with an endoscopic diagnosis of esophageal foreign bodies. Results. This pathology was more commonly found in young adult dogs and in small breeds. This pathology was present for the first time in the Portuguese Warren Hound, which was also the breed with the highest risk. Conclusions. The results obtained in this investigation are in agreement with the previous description of a patient that presents esophageal foreign bodies. Also, the Portuguese Warren Hound was found to be predisposed to this problem, with a higher risk factor than other breeds previously mentioned in the literature. To prevent esophageal foreign bodies, dogs should be fed raw meat and bones, especially small breeds. This pathology should always be kept in mind in dogs with esophagitis symptomology regardless of age, although it is most common in young adult dogs.peerReviewe