Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning

Intestine segmentation with small computational cost for diagnosis assistance of ileus and intestinal obstruction.- Generation of Patient-Specific, Ligamentoskeletal, Finite Element Meshes for Scoliosis Correction Planning.- Bayesian Graph Neural Networks For EEG-based Emotion Recognition.- ViTBIS: Vision Transformer for Biomedical Image Segmentation.- Attention-guided pancreatic duct segmentation from abdominal CT volumes.- Development of the Next Generation Hand-Held Doppler With Waveform Phasicity Predictive Capabilities Using Deep Learning.- Learning from mistakes: an error-driven mechanism to improve segmentation performance based on expert feedback.- TMJOAI: an artificial web-based intelligence tool for early diagnosis of the Temporomandibular Joint Osteoarthritis.- COVID-19 Infection Segmentation from Chest CT Images Based on Scale Uncertainty.- Multi-task Federated Learning for Heterogeneous Pancreas Segmentation.- Federated Learning in the Cloud for Analysis of Medical Images- Experience with Open Source Frameworks.- On the Fairness of Swarm Learning in Skin Lesion Classification.- Lessons learned from the development and application of medical imaging-based AI technologies for combating COVID-19: why discuss, what next.- The Role of Pleura and Adipose in Lung Ultrasound AI.- DuCN: Dual-children Network for Medical Diagnosis and Similar Case Recommendation towards COVID-19.- Data imputation and reconstruction of distributed Parkinson's disease clinical assessments: A comparative evaluation of two aggregation algorithms.- Defending Medical Image Diagnostics against Privacy Attacks using Generative Methods: Application to Retinal Diagnostics.