258 documents found, page 1 of 26
A statistical duality for Random Matching of Agents
Yannacopoulos, Athanasios; Oliveira, Bruno; Ferreira, Miguel; Martins, José; Pinto, AlbertoWe propose a statistical duality among the preferences and endowments of the agents. Under this duality, the logarithmic prices of random trades among agents in a decentralized economy converge in expectation to the logarithm of the Walrasian equilibrium price in a centralized economy.
General Physicochemical Parameters, Phenolic Composition, and Varietal Aromatic...
Jordão, António; Correia, Ana Cristina; Martins, Bárbara; Oliveira, BrunoPico Island is one of the islands of the Azores archipelago located in the North Atlantic Ocean, where there are very specific conditions for vine cultivation. In this context, there is scarce knowledge related to grape ripening under these conditions. Thus, the aim of this study was to evaluate several physicochemical parameters, the phenolic composition, antioxidant capacity, and varietal aromatic potential, ...
A digital communication system for occupational safety and health: requirements...
Ferreira, Joana; Barros, Mariana; Constantino, Gonçalo; Cavadas, Rodrigo; Rebelo, José; Oliveira, Bruno; Rodrigues, MatildeShifting the communication process in the Occupational Safety and Health (OSH) field to digital can bring advantages to risk management. A digital communication system can help ensure that all workers find it easier to report hazards, accidents, and near misses. Additionally, it can make possible access to several prevention information. Since companies typically lack this type of solution, this work aimed to i...
Design optimization of medical robotic systems based on task performance metric...
Oliveira, Bruno; Morais, Pedro André Gonçalves; Torres, Helena R.; Fonseca, Jaime C.; Vilaça, João L.While designing an end-effector tool for a specific task using an already available robotic arm is a common strategy for developing robot-based solutions, it is subject to the designer's subjective biases, especially in the medical robotics field. Consequently, this approach can result in suboptimal solutions that may limit the performance of the robotic arm and the overall system. This work introduces a novel ...
Infant head and brain segmentation from magnetic resonance images using fusion-...
Torres, Helena; Oliveira, Bruno; Morais, Pedro; Fritze, Anne; Hahn, Gabriele; Rudiger, Mario; Fonseca, Jaime; Vilaça, JoãoMagnetic resonance (MR) imaging is widely used for assessing infant head and brain development and for diagnosing pathologies. The main goal of this work is the development of a segmentation framework to create patient-specific head and brain anatomical models from MR images for clinical evaluation. The proposed strategy consists of a fusion-based Deep Learning (DL) approach that combines the information of dif...
Deep-DM: Deep-driven deformable model for 3D image segmentation using limited data
Torres, Helena; Oliveira, Bruno; Fritze, Anne; Birdir, Cahit; Rudiger, Mario; Fonseca, Jaime; Morais, Pedro; Vilaça, JoãoObective - Medical image segmentation is essential for several clinical tasks, including diagnosis, surgical and treatment planning, and image-guided interventions. Deep Learning (DL) methods have become the state-of-the-art for several image segmentation scenarios. However, a large and well-annotated dataset is required to effectively train a DL model, which is usually difficult to obtain in clinical practice,...
Dual consistency loss for contour-aware segmentation in medical images
Torres, Helena R.; Oliveira, Bruno; Fonseca, Jaime C.; Morais, Pedro André Gonçalves; Vilaça, João L.Medical image segmentation is a paramount task for several clinical applications, namely for the diagnosis of pathologies, for treatment planning, and for aiding image-guided surgeries. With the development of deep learning, Convolutional Neural Networks (CNN) have become the state-of-the-art for medical image segmentation. However, issues are still raised concerning the precise object boundary delineation, sin...
Deep learning networks for breast lesion classification in ultrasound images: a...
Ferreira, Margarida R.; Torres, Helena R.; Oliveira, Bruno; Araújo, Augusto R. V. F. de; Morais, Pedro; Novais, Paulo; Vilaça, João L.Accurate lesion classification as benign or malignant in breast ultrasound (BUS) images is a critical task that requires experienced radiologists and has many challenges, such as poor image quality, artifacts, and high lesion variability. Thus, automatic lesion classification may aid professionals in breast cancer diagnosis. In this scope, computer-aided diagnosis systems have been proposed to assist in medical...
Overcoming traditional ETL systems architectural problems using a service-orien...
Oliveira, Bruno; Oliveira, Óscar; Belo, OrlandoDeveloping analytical systems imposes several challenges related not only to the amount and heterogeneity of the involved data but also to the constant need to readapt and evolve to overcome new business challenges. Data are a determinant factor in the success of analytical and decision-making applications, being its nature, availability, and quality, crucial aspects for planning and structuring populating anal...
A multi-task convolutional neural network for classification and segmentation o...
Oliveira, Bruno; Torres, Helena R; Morais, Pedro; Veloso, Fernando; Baptista, António L.; Fonseca, Jaime C.; Vilaça, João L.Chronic Venous Disorders (CVD) of the lower limbs are one of the most prevalent medical conditions, affecting 35% of adults in Europe and North America. Due to the exponential growth of the aging population and the worsening of CVD with age, it is expected that the healthcare costs and the resources needed for the treatment of CVD will increase in the coming years. The early diagnosis of CVD is fundamental in t...