Implementation and application of Retinex algorithms to the preprocessing of retinography color images

La retinopatía diabética es una enfermedad causada por complicaciones de la retina, con evolución progresiva. Esta patología se detecta en las imágenes de fondo de ojo que, en la mayoría de los casos, presentan iluminación no uniforme. En este trabajo se implementaron y aplicaron cuatro algoritmos de la teoría Retinex a imágenes de fondo de ojo, con el fin de proporcionar una mejor iluminación, para una posterior visualización o procesamiento, buscando detectar con mayor exactitud la presencia o no de la enfermedad y poder hacer un seguimiento más acertado.Diabetic retinopathy is a disease caused by complications of the retina, with progressive evolution. This pathology is detected on the fundus eye images, which in most cases have non-uniform illumination. In this paper four type of algorithms, based on the Retinex theory, were implemented and applied to fundus images in order to provide better illumination for later visualization or processing. The purpose was to find more accuracy to detect the presence or not of the disease and thus to get a more accurate approach of diagnosis

Detección temprana de patologías diabéticas oculares en retinografías utilizando un sistema multiagentes

La Retinopatía Diabética es la complicación que suele terminar con la ceguera si los pacientes que no son tratados precozmente. Por este motivo los sistemas computacionales que ayuden a la toma de decisiones tempranas, surgen como una potencial herramienta. En este trabajo se presenta el diseño y desarrollo de un sistema multiagentes, desarrolado en JADE y diseñado mediante GAIA, para el análisis de imágenes de retina de fondo ocular. Se presenta una descripción del trabajo de cada uno de los agentes que analizan y brindan información acerca la presencia o no de signos patológicos de Edema Macular Diabético.Sociedad Argentina de Informática e Investigación Operativ

Detección temprana de patologías diabéticas oculares en retinografías utilizando un sistema multiagentes

La Retinopatía Diabética es la complicación que suele terminar con la ceguera si los pacientes que no son tratados precozmente. Por este motivo los sistemas computacionales que ayuden a la toma de decisiones tempranas, surgen como una potencial herramienta. En este trabajo se presenta el diseño y desarrollo de un sistema multiagentes, desarrolado en JADE y diseñado mediante GAIA, para el análisis de imágenes de retina de fondo ocular. Se presenta una descripción del trabajo de cada uno de los agentes que analizan y brindan información acerca la presencia o no de signos patológicos de Edema Macular Diabético.Sociedad Argentina de Informática e Investigación Operativ

Detección temprana de patologías diabéticas oculares en retinografías utilizando un sistema multiagentes

La Retinopatía Diabética es la complicación que suele terminar con la ceguera si los pacientes que no son tratados precozmente. Por este motivo los sistemas computacionales que ayuden a la toma de decisiones tempranas, surgen como una potencial herramienta. En este trabajo se presenta el diseño y desarrollo de un sistema multiagentes, desarrolado en JADE y diseñado mediante GAIA, para el análisis de imágenes de retina de fondo ocular. Se presenta una descripción del trabajo de cada uno de los agentes que analizan y brindan información acerca la presencia o no de signos patológicos de Edema Macular Diabético.Sociedad Argentina de Informática e Investigación Operativ

Optimal Transport-based Graph Matching for 3D retinal OCT image registration

Registration of longitudinal optical coherence tomography (OCT) images assists disease monitoring and is essential in image fusion applications. Mouse retinal OCT images are often collected for longitudinal study of eye disease models such as uveitis, but their quality is often poor compared with human imaging. This paper presents a novel but efficient framework involving an optimal transport based graph matching (OT-GM) method for 3D mouse OCT image registration. We first perform registration of fundus-like images obtained by projecting all b-scans of a volume on a plane orthogonal to them, hereafter referred to as the x-y plane. We introduce Adaptive Weighted Vessel Graph Descriptors (AWVGD) and 3D Cube Descriptors (CD) to identify the correspondence between nodes of graphs extracted from segmented vessels within the OCT projection images. The AWVGD comprises scaling, translation and rotation, which are computationally efficient, whereas CD exploits 3D spatial and frequency domain information. The OT-GM method subsequently performs the correct alignment in the x-y plane. Finally, registration along the direction orthogonal to the x-y plane (the z-direction) is guided by the segmentation of two important anatomical features peculiar to mouse b-scans, the Internal Limiting Membrane (ILM) and the hyaloid remnant (HR). Both subjective and objective evaluation results demonstrate that our framework outperforms other well-established methods on mouse OCT images within a reasonable execution time

Penyelesaian Masalah Penjadwalan Job-Majemuk dengan Pemakaian Sumberdaya- Majemuk Menggunakan Algoritma Genetika

Scheduling problems with regard to the problem of determining the order to carry out a number of tasks. This issue covers a wide range of areas such as manufacturing, installation project, production planning, hospital management and reservation system. This problem can be seen as an optimization problem of dealing with a number of constraints. An increase in the complexity of the problem requires the existence of an efficient and effective techniques. This study addresses the issue of scheduling multiple job-where there are several different types of resources that are working on an operation or activity simultaneously. Genetic algorithms are developed to solve these problems. Genetic algorithm testing performed against a number of hipotetik example. The output agoritma of genetics compared against optimal technique of the output and the output algorithm based on Lagrange relaxation on the same issue. The results of the comparison with optimal techniques and algorithms based on Lagrange relaxation indicates a significant improvement of computing efficiency, but nevertheless occur a little decrease in effectiveness

The Educational Sandbox: augmented reality a new resource for teaching

En este artículo presentamos el proyecto Arenero Educativo que utiliza la tecnología de Realidad Aumentada para implementar un recurso para la enseñanza de las matemáticas y las ciencias naturales. Esta instalación usa una cámara infrarroja para leer la superficie tridimensional de la arena y después dibujar sobre ella curvas de nivel y cuerpos de agua que se transforman cuando el usuario interactúa con la arena. Describimos con detalle las nuevas posibilidades de su interfaz novedosa y su implementación técnica. Detallamos también nuestra propuesta didáctica y reflexionamos acerca de la importancia de establecer una ruta de implementación accesible. Finalmente, discutimos acerca de la importancia del MediaLab de la Universidad de Salamanca como agente dinamizador de este tipo de proyectos multidisciplinares.In this paper, we present the project Educational Sandbox that uses the Augmented Reality to implement a resource for the teaching of mathematics and natural sciences. This installation uses an infrared camera to read the three-dimensional surface of the sand and then dr aw on it contours and bodies of water that are transformed when the user interacts with the sand. We describe in detail, the new possibilities of this novel interface and its technical implementation. We also describe our didactic proposal for this install ation and reflect on the importance of establishing an accessible implementation route. Finally, we discuss about the importance of the MediaLab of the University of Salamanca as a dynamizing agent of this type of multidisciplinary projects

Single-Model and Any-Modality for Video Object Tracking

In the realm of video object tracking, auxiliary modalities such as depth, thermal, or event data have emerged as valuable assets to complement the RGB trackers. In practice, most existing RGB trackers learn a single set of parameters to use them across datasets and applications. However, a similar single-model unification for multi-modality tracking presents several challenges. These challenges stem from the inherent heterogeneity of inputs -- each with modality-specific representations, the scarcity of multi-modal datasets, and the absence of all the modalities at all times. In this work, we introduce Un-Track, a Unified Tracker of a single set of parameters for any modality. To handle any modality, our method learns their common latent space through low-rank factorization and reconstruction techniques. More importantly, we use only the RGB-X pairs to learn the common latent space. This unique shared representation seamlessly binds all modalities together, enabling effective unification and accommodating any missing modality, all within a single transformer-based architecture. Our Un-Track achieves +8.1 absolute F-score gain, on the DepthTrack dataset, by introducing only +2.14 (over 21.50) GFLOPs with +6.6M (over 93M) parameters, through a simple yet efficient prompting strategy. Extensive comparisons on five benchmark datasets with different modalities show that Un-Track surpasses both SOTA unified trackers and modality-specific counterparts, validating our effectiveness and practicality. The source code is publicly available at https://github.com/Zongwei97/UnTrack.Comment: Accepted by CVPR202