A Detection Method of Ectocervical Cell Nuclei for Pap test Images, Based on Adaptive Thresholds and Local Derivatives

Cervical cancer is one of the main causes of death by disease worldwide. In Peru, it holds the first place in frequency and represents 8% of deaths caused by sickness. To detect the disease in the early stages, one of the most used screening tests is the cervix Papanicolaou test. Currently, digital images are increasingly being used to improve Pap test efficiency. This work develops an algorithm based on adaptive thresholds, which will be used in Pap smear assisted quality control software. The first stage of the method is a pre-processing step, in which noise and background removal is done. Next, a block is segmented for each one of the points selected as not background, and a local threshold per block is calculated to search for cell nuclei. If a nucleus is detected, an artifact rejection follows, where only cell nuclei and inflammatory cells are left for the doctors to interpret. The method was validated with a set of 55 images containing 2317 cells. The algorithm successfully recognized 92.3% of the total nuclei in all images collected.Revisón por pare

Device to evaluate cleanliness of fiber optic connectors using image processing and neural networks

This work proposes a portable, handheld electronic device, which measures the cleanliness in fiber optic connectors via digital image processing and artificial neural networks. Its purpose is to reduce the evaluation subjectivity in visual inspection done by human experts. Although devices with this purpose already exist, they tend to be cost-prohibitive and do not take advantage of neither image processing nor artificial intelligence to improve their results. The device consists of an optical microscope for fiber optic connector analysis, a digital camera adapter, a reduced-board computer, an image processing algorithm, a neural network algorithm and an LCD screen for equipment operation and results visualization. The image processing algorithm applies grayscale histogram equalization, Gaussian filtering, Canny filtering, Hough transform, region of interest segmentation and obtaining radiometric descriptors as inputs to the neural network. Validation consisted of comparing the results by the proposed device with those obtained by agreeing human experts via visual inspection. Results yield an average Cohen's Kappa of 0.926, which implies a very satisfactory performance by the proposed device

Robot Arm Control System for Assisted Feeding of People with Disabilities in their Upper Limbs

This work proposes a robot arm control system for assisted feeding of people with reduced functionality in their upper limbs. It aims at improving their quality of life by helping users recover their independence when feeding, aided by the proposed system. Previous research presents solutions that often lack functionality to meet the user’s needs, such as a lack of emergency functions or the use of passive feeding techniques, due to the absence of adequate human-robot interaction. The proposed solution involves the design of an interface adapter between the robot arm and the spoon, for the correct transport and positioning of the food. Moreover, a PD-type electronic controller is implemented for the robot arm; it includes gravity compensation and trajectories defined from the detection of the user's position. Additionally, the system has two safety features: an emergency button and a proximity warning that triggers when undesired objects are too close to the robot arm. The proposed system was validated through position tests and interaction with people using rice and oatmeal. When carrying out the tests with rice, 80% success was obtained, while in the case of oatmeal, 98.9% success was achieved

Un método automático de extracción de información de imágenes digitales basado en la detección de posicionamiento de marcas ópticas a partir de distancias euclidianas y redes neuronales

Se plantea un método de reconocimiento de marcas ópticas utilizando una cámara WEB a través del presente trabajo. El mismo se orienta al reconocimiento del código y la nota de un estudiante en un cuadernillo de evaluación. Las marcas se generan en el cuadernillo utilizando un lapicero. Se utilizan algoritmos y técnicas de procesamiento de imágenes como el filtrado espacial, umbralización, segmentación, descripción y reconocimiento a través de redes neuronales. El método propuesto permite automatizar el ingreso de notas académicas a una base de datos, sin alterar significativamente el formato de los cuadernillos utilizado en las evaluaciones de los estudiantes. Los resultados obtenidos demuestran que el método propuesto alcanza un error máximo del 2% en el proceso de reconocimiento

An Algorithm for Plant Disease Visual Symptom Detection in Digital Images Based on Superpixels

Quantifying diseased areas in plant leaves is an important procedure in agriculture, as it contributes to crop monitoring and decision-making for crop protection. It is, however, a time-consuming and very subjective manual procedure whose automation is, therefore, highly expected. This work proposes a new method for the automatic segmentation of diseased leaf areas. The method used the Simple Linear Iterative Clustering (SLIC) algorithm to group similar-color pixels together into regions called superpixels. The color features of superpixel clusters were used to train artificial neural networks (ANNs) for the classification of superpixels as healthy or not healthy. These network parameters were heuristically tuned by choosing the network with the best classification performance to obtain the automatic segmentation of the diseased areas. The performance of the classifier was measured by comparing its automatic segmentations with those manually made from a database with public and private images divided into nine groups by visual symptom and plant. The mean error of the area obtained was always below 11%, and the average F-score was 0.67, which is higher than that found by the other two approaches reported in the literature (0.57 and 0.58) and used here for comparison

A novel algorithm for detection of tuberculosis bacilli in sputum smear fluorescence images

This work proposes an algorithm aimed at recognizing and accounting Koch bacilli in digital images of microbiological sputum samples stained with auramine, in order to determine the degree of concentration and the state of the disease (tuberculosis). The algorithm was developed with the main objective of maximizing the sensitivity and specificity of the analysis of microbiological samples (recognition and counting of bacilli) according to each preparation method (direct and diluted pellets) in order to reduce the subjectivity of the visual inspection applied by the specialist at the time of analyzing the samples. The proposed algorithm consists of a background removal, an image improvement stage based on consecutive morphological closing operations, a segmentation stage of objects of interest based on thresholdization and a classification stage based on SVM. Each algorithmic stage was developed taking into account the method of preparation of the sample to be processed, being this aspect the main contribution of the proposed work, since it was possible to achieve very satisfactory results in terms of specificity and sensitivity. In this context, sensitivity levels of 91.24% and 93.79% were obtained. Specificity levels of 90.33% and 94.85% were also achieved for direct and diluted pellet methods respectively

An algorithm for detection of tuberculosis bacilli in Ziehl-Neelsen sputum smear images

This work proposes an algorithm oriented to the detection of tuberculosis bacilli in digital images of sputum samples, inked with the Ziehl Neelsen method and prepared with the direct, pellet and diluted pellet methods. The algorithm aims at automating the optical analysis of bacilli count and the calculation of the concentration level. Several algorithms have been proposed in the literature with the same objective, however, in no case is the performance in sensitivity and specificity evaluated for the 3 preparation methods. The proposed algorithm improves the contrast of the colors of interest, then thresholds the image and segments by labeling the objects of interest (bacilli). Each object then has its geometrical descriptors and photometric descriptors. With all this, a characteristic vector is formed, which are used in the training and classification process of an SVM. For the training 225 images obtained by the 3 preparation methods were used. The proposed algorithm reached, for the direct method, a sensitivity level of 93.67% and a specificity level of 89.23%. In the case of the Pellet method, a sensitivity of 92.13% and a specificity of 82.58% was obtained, while for diluted Pellet the sensitivity was 92.81% and the specificity 83.61%

Cost-effectiveness of groundwater conservation measures: A multi-level analysis with policy implications

Groundwater in Spain, as in other arid and semiarid countries worldwide, has been widely used in the expansion of irrigated agriculture. In the Spanish Mancha Occidental aquifer, the excessive, and sometimes illegal, water abstraction for irrigation has promoted outstanding socioeconomic development in the area, but it has also resulted in exploitation of the aquifer and degradation of valuable wetlands. Water policies implemented in the region have not yet managed to restore the aquifer and face strong social opposition. This paper uses a multi-scale modeling approach to explore the environmental and socio-economic impacts of alternative water conservation measures at the farm and basin levels. It also analyzes their comparative cost-effectiveness to help policy makers identify the least costly policy option for achieving the goal of the Mancha Occidental aquifer's sustainability. To conduct this analysis, a Mathematical Programming Model has been developed to simulate: the closing-up and taxed-legalization of unlicensed wells, uniform volumetric and block-rate water prices, water quotas, and water markets. Aggregate results show that net social costs are not substantially different across policy option, so none of the considered policy options will be clearly more cost-effective than the others. However, there are significant differences between private and public costs (at the farm and sub-basin levels), which will be critical for determining the application in practice of these policies. Results show that controlling illegal water mining (through the legalization of unlicensed wells) is necessary, but is not sufficient to recover the aquifer. Rather, effective water management in this area will require the implementation of other water management policies as well. Among them, uniform volumetric and block-rate water pricing policies will entail the lowest net social cost, but will produce important income losses in the smallest and most water-intensive farms, which might put at risk the viability of these farms and the social acceptance of the policies. Further investigations on social costs, policy enforcement capacity and public participation in water management are highly recommende

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field