Educational Web Tool for Digital Image Processing

En este trabajo se propuso un modelo de una herramienta que ayuda al aprendizaje en el área de procesamiento digital de imágenes dirigido a los alumnos de grado y postgrado de la Facultad Politécnica. Además, se llevó a cabo la implementación de la primera fase de la herramienta.CONACYT – Consejo Nacional de Ciencia y TecnologíaPROCIENCI

Automatic Diagnosis of Ocular Toxoplasmosis from Fundus Images with Residual Neural Networks.

Ocular toxoplasmosis (OT) is commonly diagnosed through the analysis of fundus images of the eye by a specialist. Despite Deep Learning being widely used to process and recognize pathologies in medical images, the diagnosis of ocular toxoplasmosis(OT) has not yet received much attention. A predictive computational model is a valuable time-saving option if used as a support tool for the diagnosis of OT. It could also help diagnose atypical cases, being particularly useful for ophthalmologists who have less experience. In this work, we propose the use of a deep learning model to perform automatic diagnosis of ocular toxoplasmosis from images of the eye fundus. A pretrained residual neural network is fine-tuned on a dataset of samples collected at the medical center of Hospital de Clínicas in Asunción, Paraguay. With sensitivity and specificity rates equal to 94% and 93%,respectively, the results show that the proposed model is highly promising. In order to replicate the results and advance further in this area of research, an open data set of images of the eye fundus labeled by ophthalmologists is made available.CONACYT - Consejo Nacional de Ciencia y TecnologíaPROCIENCI

Dataset from fundus images for the study of diabetic retinopathy.

This article presents a database containing 757 color fun dus images acquired at the Department of Ophthalmology of the Hospital de Clínicas, Facultad de Ciencias Médicas (FCM), Universidad Nacional de Asunción (UNA), Paraguay. Firstly, the retinal images were acquired with a clinical procedure presented in this paper. The acquisition of the retinographies was made through the Visucam 500 camera of the Zeiss brand. Next, two expert ophthalmologists have classified the dataset. These data can help physicians and researchers in the detection of cases of Non-Proliferative Diabetic Retinopa thy (NPDR) and Proliferative Diabetic Retinopathy (PDR), in their different stages. The dataset generated will be useful for ophthalmologists and researchers to work on automatic detection algorithms for Diabetic Retinopathy (DR).CONACYT - Consejo Nacional de Ciencia y TecnologíaPROCIENCI

Redundancy Is Not Necessarily Detrimental in Classification Problems

In feature selection, redundancy is one of the major concerns since the removal of redun dancy in data is connected with dimensionality reduction. Despite the evidence of such a connection, few works present theoretical studies regarding redundancy. In this work, we analyze the effect of redundant features on the performance of classification models. We can summarize the contribution of this work as follows: (i) develop a theoretical framework to analyze feature construction and selection, (ii) show that certain properly defined features are redundant but make the data linearly separable, and (iii) propose a formal criterion to validate feature construction methods. The results of experiments suggest that a large number of redundant features can reduce the classification error. The results imply that it is not enough to analyze features solely using criteria that measure the amount of information provided by such features.CONACYT - Consejo Nacional de Ciencia y TecnologíaPROCIENCI

The genomic basis of color pattern polymorphism in the Harlequin ladybird

© 2018 The Authors Many animal species comprise discrete phenotypic forms. A common example in natural populations of insects is the occurrence of different color patterns, which has motivated a rich body of ecological and genetic research [1–6]. The occurrence of dark, i.e., melanic, forms displaying discrete color patterns is found across multiple taxa, but the underlying genomic basis remains poorly characterized. In numerous ladybird species (Coccinellidae), the spatial arrangement of black and red patches on adult elytra varies wildly within species, forming strikingly different complex color patterns [7, 8]. In the harlequin ladybird, Harmonia axyridis, more than 200 distinct color forms have been described, which classic genetic studies suggest result from allelic variation at a single, unknown, locus [9, 10]. Here, we combined whole-genome sequencing, population-based genome-wide association studies, gene expression, and functional analyses to establish that the transcription factor Pannier controls melanic pattern polymorphism in H. axyridis. We show that pannier is necessary for the formation of melanic elements on the elytra. Allelic variation in pannier leads to protein expression in distinct domains on the elytra and thus determines the distinct color patterns in H. axyridis. Recombination between pannier alleles may be reduced by a highly divergent sequence of ∼170 kb in the cis-regulatory regions of pannier, with a 50 kb inversion between color forms. This most likely helps maintain the distinct alleles found in natural populations. Thus, we propose that highly variable discrete color forms can arise in natural populations through cis-regulatory allelic variation of a single gene. More than 200 distinct color forms have been described in natural populations of the harlequin ladybird, Harmonia axyridis. Gautier et al. show that this variation is controlled by the transcription factor Pannier. Pannier is necessary to produce black pigment, and its expression pattern prefigures the coloration pattern in each color form

EDOSI : un systeme d'etude du deplacement d'objets a partir d'une sequence d'images

SIGLECNRS T Bordereau / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Segmentation Methodology of Table-Form Documents

This article presents a method for the automatic extraction of the contents of passive and/or active cells in forms. The approach is based on the analysis and recognition of the types of intersection of the lines that make up such cells. Very little a priori knowledge of the form is required. The performance of this approach depends on the correction module mechanisms for detection and correction of errors generated during the intersection identification phase. The potentialities and advantages of this approach are described and illustrated with tests carried out on different form bases.