12 research outputs found

    Retinal image analysis: Image processing and feature extraction oriented to the clinical task

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    Medical digital imaging has become a key element of modern health care procedures. It provides visual documentation and a permanent record for the patients, and most important the ability to extract quantitative information about many diseases. Modern ophthalmology relies on the advances in digital imaging and computing power. In this paper we present an overview of the results from the doctoral dissertation by Andrés G. Marrugo. This dissertation contributes to the digital analysis of retinal images and the problems that arise along the imaging pipeline of fundus photography, a field that is commonly referred to as retinal image analysis. We have dealt with and proposed solutions to problems that arise in retinal image acquisition and longitudinal monitoring of retinal disease evolution. Specifically, non-uniform illumination compensation, poor image quality, automated focusing, image segmentation, change detection, space-invariant (SI) and space-variant (SV) blind deconvolution (BD). Digital retinal image analysis can be effective and cost-efficient for disease management, computeraided diagnosis, screening and telemedicine and applicable to a variety of disorders such as glaucoma, macular degeneration, and retinopathy. © 2017. Sociedad Española de Óptica. All right reserved

    Developing a Robust Acquisition System for Fringe Projection Profilometry

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    Since Fringe Projection Profilometry (FPP) is an intensity-based coding strategy, it is prone to improper optical setup arrangement, surface texture and reflectance, uneven illumination distribution, among others. These conditions introduce errors in phase retrieval which lead to an inaccurate 3-D reconstruction. In this paper, we describe a dynamic approach toward a robust FPP acquisition in challenging scenes and objects. Our aim is to acquire the best possible fringe pattern image by adjusting the object closer to an ideal system-object setup. We describe the software implementation of our method and the interface design using LabVIEW. Experimental results demonstrate that the proposed method greatly reduces sources of error in 3-D reconstruction. © Published under licence by IOP Publishing Ltd.Universidad Tecnológica de Pereira, UTP: C2018P018, C2018P005 538871552485 Departamento Administrativo de Ciencia, Tecnología e Innovación, COLCIENCIASThis work has been partly funded by Colciencias (Fondo Nacional de Financiamiento para la Ciencia, la Tecnología y la Innovación Francisco José de Caldas) project 538871552485, and by Universidad Tecnológica de Bolívar projects C2018P005 and C2018P018. Authors thank Dirección de Investigaciones, Universidad Tecnológica de Bolívar for the support. J. Pineda thanks Universidad Tecnológica de Bolívar for a Masters degree scholarship

    Robust automated reading of the skin prick test via 3D imaging and parametric surface fitting

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    The conventional reading of the skin prick test (SPT) for diagnosing allergies is prone to inter- and intra-observer variations. Drawing the contours of the skin wheals from the SPT and scanning them for computer processing is cumbersome. However, 3D scanning technology promises the best results in terms of accuracy, fast acquisition, and processing. In this work, we present a wide-field 3D imaging system for the 3D reconstruction of the SPT, and we propose an automated method for the measurement of the skin wheals. The automated measurement is based on pyramidal decomposition and parametric 3D surface fitting for estimating the sizes of the wheals directly. We proposed two parametric models for the diameter estimation. Model 1 is based on an inverted Elliptical Paraboloid function, and model 2 on a super-Gaussian function. The accuracy of the 3D imaging system was evaluated with validation objects obtaining transversal and depth accuracies within ± 0.1 mm and ± 0.01 mm, respectively. We tested the method on 80 SPTs conducted in volunteer subjects, which resulted in 61 detected wheals. We analyzed the accuracy of the models against manual reference measurements from a physician and obtained that the parametric model 2 on average yields diameters closer to the reference measurements (model 1: -0.398 mm vs. model 2: -0.339 mm) with narrower 95% limits of agreement (model 1: [-1.58, 0.78] mm vs. model 2: [-1.39, 0.71] mm) in a Bland-Altman analysis. In one subject, we tested the reproducibility of the method by registering the forearm under five different poses obtaining a maximum coefficient of variation of 5.24% in the estimated wheal diameters. The proposed method delivers accurate and reproducible measurements of the SPT. © 2019 Pineda et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Departamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS), COLCIENCIAS: 538871552485 C2018P018, C2018P005This study was supported by Colciencias (www.colciencias.gov.co, Grant 538871552485) and by Universidad Tecnol?gica de Bolivar (www.utb.edu.co, Grants C2018P005 and C2018P018), Colombia

    A Structure-from-Motion Pipeline for Generating Digital Elevation Models for Surface-Runoff Analysis

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    Digital Elevation Models (DEMs) are used to derive information from the morphology of a land. The topographic attributes obtained from the DEM data allow the construction of watershed delineation useful for predicting the behavior of systems and for studying hydrological processes. Imagery acquired from Unmanned Aerial Vehicles (UAVs) and 3D photogrammetry techniques offer cost-effective advantages over other remote sensing methods such as LIDAR or RADAR. In particular, a high spatial resolution for measuring the terrain microtopography. In this work, we propose a Structure from Motion (SfM) pipeline using UAVs for generating high-resolution, high-quality DEMs for developing a rainfall-runoff model to study flood areas. SfM is a computer vision technique that simultaneously estimates the 3D coordinates of a scene and the pose of a camera that moves around it. The result is a 3D point cloud which we process to obtain a georeference model from the GPS information of the camera and ground control points. The pipeline is based on open source software OpenSfM and OpenDroneMap. Encouraging experimental results on a test land show that the produced DEMs meet the metrological requirements for developing a surface-runoff model. © Published under licence by IOP Publishing Ltd.This work has been partly funded by Universidad Tecnológica de Bolívar project (FI2006T2001). The authors thank Direccion de Investigaciones Universidad Tecnologica de Bolivar for their support

    Fringe quality map for fringe projection profilometry in LabVIEW

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    The phase retrieval process is mainly affected by local shadows, irregular surface brightness and fringe discontinuities. To overcome these problems, image-processing strategies are carried out such as binary masks, interpolation techniques, and filtering. Similarly, many unwrapping algorithms have been developed to handle phase unwrapping errors in two-dimensional regions. The presence of error-prone areas can be visualized during the acquisition stage avoiding the use of image processing strategies and sophisticated phase unwrapping algorithms, which in many cases represent high computational costs and long execution times. To help overcome these problems, we propose a Fringe Quality Map based on a phase residue analysis to estimate error-prone areas during acquisition. The software was fully implemented in LabVIEW, and we provide the software as supplementary material. Experimental results demonstrate that the proposed method estimates areas with poor contrast, which lead to unwrapping errors, as well as phase errors in a more complex 3D shape. © Sociedad Española de Óptica

    Métodos de calibración cámara-proyector con compensación de distorsiones geométricas en perfilometría por proyección de franjas: Un estudio comparativo

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    The calibration methods most used in fringe projection profilometry are based on models of least squares adjustment and stereo vision techniques. However, the geometric distortions of the projector and camera lenses introduce imprecision in certain regions of the 3D reconstruction. In this paper, we perform a comparative study between the second order polynomial adjustment method and the stereo calibration method applying lens distortion compensation. The experimental results show that in the stereo calibration the incidence of the distortions in the 3D reconstruction is significant. In contrast, in the proposed polynomial calibration, reconstruction errors are associated with the calibrated volume, typically low within the calibration volume. © Sociedad Española de óptica.Los métodos de calibración más usados en perfilometría por proyección de franjas están basados en modelos de ajustes por mínimos cuadrados y técnicas de visión estéreo. Sin embargo, las distorsiones geométricas de los lentes del proyector y de la cámara introducen imprecisión en ciertas regiones de la reconstrucción 3D. En este trabajo realizamos un estudio comparativo entre el método de ajuste polinomial de segundo orden y el método de calibración estéreo aplicando compensación de distorsiones. Los resultados experimentales muestran que en la calibración estéreo la incidencia de las distorsiones en la reconstrucción 3D es significativa. En cambio, en la calibración polinomial propuesta, los errores de reconstrucción están asociados al volumen calibrado. © Sociedad Española de óptica

    Anemia prevalence in women of reproductive age in low- and middle-income countries between 2000 and 2018

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    Anemia is a globally widespread condition in women and is associated with reduced economic productivity and increased mortality worldwide. Here we map annual 2000–2018 geospatial estimates of anemia prevalence in women of reproductive age (15–49 years) across 82 low- and middle-income countries (LMICs), stratify anemia by severity and aggregate results to policy-relevant administrative and national levels. Additionally, we provide subnational disparity analyses to provide a comprehensive overview of anemia prevalence inequalities within these countries and predict progress toward the World Health Organization’s Global Nutrition Target (WHO GNT) to reduce anemia by half by 2030. Our results demonstrate widespread moderate improvements in overall anemia prevalence but identify only three LMICs with a high probability of achieving the WHO GNT by 2030 at a national scale, and no LMIC is expected to achieve the target in all their subnational administrative units. Our maps show where large within-country disparities occur, as well as areas likely to fall short of the WHO GNT, offering precision public health tools so that adequate resource allocation and subsequent interventions can be targeted to the most vulnerable populations.Peer reviewe

    Anemia prevalence in women of reproductive age in low- and middle-income countries between 2000 and 2018

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