Experiencia de realización de proyectos fin de carrera en el área de los sistemas multi-agente

El GruSMA (Grupo de trabajo en Sistemas Multi-Agente) proporciona un entorno en el que alumnos de primer y segundo ciclo de Ingeniería Informática de la Universidad Rovira i Virgili (URV) pueden realizar Proyectos Fin de Carrera en el área de los Sistemas Multi-Agente. En esta ponencia describimos la motivación para su creación, su metodología de trabajo y los resultados obtenidos hasta el momento

Convexity shape constraints for retinal blood vessel segmentation and foveal avascular zone detection

Diabetic retinopathy (DR) has become a major worldwide health problem due to the increase in blindness among diabetics at early ages. The detection of DR pathologies such as microaneurysms, hemorrhages and exudates through advanced computational techniques is of utmost importance in patient health care. New computer vision techniques are needed to improve upon traditional screening of color fundus images. The segmentation of the entire anatomical structure of the retina is a crucial phase in detecting these pathologies. This work proposes a novel framework for fast and fully automatic blood vessel segmentation and fovea detection. The preprocessing method involved both contrast limited adaptive histogram equalization and the brightness preserving dynamic fuzzy histogram equalization algorithms to enhance image contrast and eliminate noise artifacts. Afterwards, the color spaces and their intrinsic components were examined to identify the most suitable color model to reveal the foreground pixels against the entire background. Several samples were then collected and used by the renowned convexity shape prior segmentation algorithm. The proposed methodology achieved an average vasculature segmentation accuracy exceeding 96%, 95%, 98% and 94% for the DRIVE, STARE, HRF and Messidor publicly available datasets, respectively. An additional validation step reached an average accuracy of 94.30% using an in-house dataset provided by the Hospital Sant Joan of Reus (Spain). Moreover, an outstanding detection accuracy of over 98% was achieved for the foveal avascular zone. An extensive state-of-the-art comparison was also conducted. The proposed approach can thus be integrated into daily clinical practice to assist medical experts in the diagnosis of DR

A color fusion model based on Markowitz portfolio optimization for optic disc segmentation in retinal images

Retinal disorders are a severe health threat for older adults because they may lead to vision loss and blindness. Diabetic patients are particularly prone to suffer from Diabetic Retinopathy. Identifying relevant structural components in color fundus images like the optic disc (OD) is crucial to diagnose retinal diseases. Automatic OD detection is complex because of its location in an area where blood vessels converge, and color distribution is uneven. Several image processing techniques have been developed for OD detection so far, but vessel segmentation is sometimes required, increasing computational complexity and time. Moreover, precise OD segmentation methods utilize complex algorithms that need special hardware or extensive labeled datasets. We propose an OD detection approach based on the Modern Portfolio Theory of Markowitz to generate an innovative color fusion model. Specifically, the training phase calculates the optimal weights for each color channel. A fusion of weighted color channels is then applied in the testing phase. This approach acts as a powerful and real-time preprocessing stage. We use four heterogeneous datasets to validate the presented methodology. Three out of four datasets are publicly available (i.e., DRIVE, Messidor, and HRF), and the last corresponds to an in–house dataset acquired from Hospital Universitari Sant Joan de Reus (Spain). Two different segmentation methods are presented and compared with state-of-the-art computer vision techniques to analyze the model performance. An outstanding accuracy and overlap above 0.9 and 80%, respectively, and a minimal execution time of 0.05 s are reached. Therefore, our model could be integrated into daily clinical practice to accelerate the diagnosis of Diabetic Retinopathy due to its simplicity, performance, and speed

A semantic multi-criteria approach to evaluate different types of energy generation technologies

Multi-Criteria Decision Aid methods are used to find the best option from a set of alternatives when multiple and conflicting criteria have to be optimized simultaneously. The evaluation of the suitability or risk of each alternative is usually performed by assigning a numerical value. However, sometimes the data required to measure a criterion may be found in the form of semantic values such as tags. This paper proposes a methodology to calculate the strength of an outranking relation for a pair of alternatives using semantic criteria following the principles of ELECTRE-III (i.e. by means of concordance and discordance indices). The preferences about semantic data are represented in an ontology by means of objective and subjective functions. The paper explains how this new methodology was applied to analyse different electricity generation technologies using environmental and economic criteria. Two scenarios are tested to show how semantic criteria may influence the final decision

Mejora de la formación en el diseño y desarrollo de software a partir de la coordinación de distintas asignaturas

Esta contribución explica el diseño e implementación de una metodología de formación puesta en marcha en el Grado de Ingeniería Informática de la Universidad Rovira i Virgili desde hace 4 años. El objetivo es mejorar las competencias prácticas de los alumnos en el diseño y desarrollo de software. Para ello se han coordinado y dado continuidad a las prácticas de tres asignaturas obligatorias de diferentes cursos. Se trata de desarrollar un mismo proyecto de software a lo largo de la carrera bajo la perspectiva de tres roles diferentes: diseñador, desarrollador y director. En segundo curso, los estudiantes ejercen el rol de desarrollador en grupos de 4 (programación, integración y prueba) bajo la supervisión por un estudiante de cuarto que ejerce el rol de director (planifica y distribuye tareas y coordina el equipo). El director también propone el diseño formal del software, que ya ha trabajado en la asignatura de tercero (rol de diseñador: análisis de requisitos y diseño). Los resultados muestran una mejora en las capacidades formativas trabajadas en las asignaturas, que se reflejan en una mejora de la calidad de la programación, mejor organización del trabajo y cumplimiento de plazos y una visión mucho más práctica del rol de director.This contribution explains the design and implementation of a teaching methodology applied during 4 years in the Computer Engineering Degree at University Rovira i Virgili. The goal is to improve the students’ practical skills on software design and development. With this purpose, we have coordinated the practical projects of three mandatory subjects of different courses. The work consists on developing the same software project in consecutive courses of the degree taking three different roles: designer, developer and director. In the subject of 2nd course, the students exercise the developer role in teams of 4 people (programming, integration and testing) under the supervision of a student of the 4th course with the director role (in charge of planning, distributing tasks and coordinating the team). The director follows the formal software design of the project he has developed in a 3rd course subject (designer role: requirements analysis and design). The results show an improvement of the skills and competences related to these 3 subjects, which include better programming quality, better team coordination and fulfilment of deadlines, as well as a much practical view of the director’s role

Validation of a diagnostic support system for diabetic retinopathy based on clinical parameters

Purpose: To validate a clinical decision support system (CDSS) that estimates risk of diabetic retinopathy (DR) and to personalize screening protocols in type 2 diabetes mellitus (T2DM) patients. Methods: We utilized a CDSS based on a fuzzy random forest, integrated by fuzzy decision trees with the following variables: current age, sex, arterial hypertension, diabetes duration and treatment, HbA1c, glomerular filtration rate, microalbuminuria, and body mass index. Validation was made using the electronic health records of a sample of 101,802 T2DM patients. Diagnosis was made by retinal photographs, according to EURODIAB guidelines and the International Diabetic Retinopathy Classification. Results: The prevalence of DR was 19,759 patients (19.98%). Results yielded 16,593 (16.31%) true positives, 72,617 (71.33%) true negatives, 3165 (3.1%) false positives, and 9427 (9.26%) false negatives, with an accuracy of 0.876 (95% confidence interval [CI], 0.858–0.886), sensitivity of 84% (95% CI, 83.46–84.49), specificity of 88.5% (95% CI, 88.29–88.72), positive predictive value of 63.8% (95% CI, 63.18–64.35), negative predictive value of 95.8% (95% CI, 95.68–95.96), positive likelihood ratio of 7.30, and negative likelihood ratio of 0.18. The type 1 error was 0.115, and the type 2 error was 0.16. Conclusions: We confirmed a good prediction rate for DR from a representative sample of T2DM in our population. Furthermore, the CDSS was able to offer an individualized screening protocol for each patient according to the calculated risk confidence value. Translational Relevance: Results from this study will help to establish a novel strategy for personalizing screening for DR according to patient risk factors.The authors thank Phil Hoddy for his language assistance and for editing and correcting the English text. Supported by Instituto de Investigaciones Carlos III (research projects PI18/00169, PI12/01535, and PI15/01150) and by the European Regional Development Fund (FEDER).The authors thank Phil Hoddy for his language assistance and for editing and correcting the English text. Supported by Instituto de Investigaciones Carlos III (research projects PI18/00169, PI12/01535, and PI15/01150) and by the European Regional Development Fund (FEDER)