262 documents found, page 1 of 27
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.
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,...
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...
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, ...
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 ...
Automated segmentation of normal and diseased coronary arteries – The ASOCA cha...
Gharleghi, Ramtin; Adikari, Dona; Ellenberger, Katy; Ooi, Sze-Yuan; Ellis, Chris; Chen, Chung-Ming; Gao Ruochen Gao, Ruochen; He, YutingCardiovascular disease is a major cause of death worldwide. Computed Tomography Coronary Angiography (CTCA) is a non-invasive method used to evaluate coronary artery disease, as well as evaluating and reconstructing heart and coronary vessel structures. Reconstructed models have a wide array of for educational, training and research applications such as the study of diseased and non-diseased coronary anatomy, m...
Rapid artificial intelligence solutions in a pandemic—The COVID-19-20 Lung CT L...
R. Roth, Holger; Xu, Ziyue; Tor-Díez, Carlos; Sanchez Jacob, Ramon; Zember, Jonathan; Molto, Jose; Li, Wenqi; Xu, Sheng; Turkbey, Baris; Turkbey, EvrimArtificial intelligence (AI) methods for the automatic detection and quantification of COVID-19 lesions in chest computed tomography (CT) might play an important role in the monitoring and management of the disease. We organized an international challenge and competition for the development and comparison of AI algorithms for this task, which we supported with public data and state-of-the-art benchmark methods....
Characterization of the Workspace and Limits of Operation of Laser Treatments f...
Oliveira, Bruno; Morais, Pedro; Torres, Helena R.; Fonseca, Jaime C.; Vilaça, João L.; Baptista, António L.The increase of the aging population brings numerous challenges to health and aesthetic segments. Here, the use of laser therapy for dermatology is expected to increase since it allows for non-invasive and infection-free treatments. However, existing laser devices require doctors’ manually handling and visually inspecting the skin. As such, the treatment outcome is dependent on the user’s expertise, which frequ...
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...