Lung Parenchyma Segmentation Based on U-Net Fused with Shape Stream
Data from the OSIC Data Repository was used to conduct this research.
Application of Neural-Controlled Differential Equations in Disease Progression Modeling Using Irregularly Sampled Multimodal Data
Data from the OSIC Data Repository was used to conduct this research.
Vision Intelligence Assisted Lung Function Estimation Based on Transformer Encoder-Decoder Network with Invertible Modeling
OSIC is mentioned in this research.
A Bayesian Neural Network-Based Method for the Extraction of a Metabolic Corrected Arterial Input Function From Dynamic [11C]PBR28 PET
Data from the OSIC Data Repository was used to conduct this research.
Neural Network Based Method for the Survival Analysis of Idiopathic Pulmonary Fibrosis Patients from a Baseline CT Acquisition
Data from the OSIC Data Repository was used to conduct this research.
Idiopathic Pulmonary Fibrosis Prognosis
Data from the OSIC Data Repository was used to conduct this research.
Sharing Data is Essential for the Future of AI in Medical Imaging
OSIC is mentioned in this research.
Lung Modelling Congress 2023
OSIC shared its expertise as part of a session that discussed “Leveling the Playing Field: How Imaging, AI & an Infinite Mindset Can Transform the
Prevent Cancer Foundation’s Quantitative Imaging Workshop (QIW) XX
OSIC discussed “Using Large, Longitudinal Databases to Predict Status of Disease Processes,” along with panelists from Columbia University; National Lung and Heart Institute/Imperial College London;
Recent Advancements in Computed Tomography Assessment of Fibrotic Interstitial Lung Diseases
OSIC is mentioned in this research.
Development and Validation of a CT-based Deep Learning Algorithm to Augment Non-invasive Diagnosis of Idiopathic Pulmonary Fibrosis
Data from the OSIC Data Repository was used to conduct this research.
A Deep Learning Algorithm for Predicting Disease Progression in Idiopathic Pulmonary Fibrosis
Data from the OSIC Data Repository was used to conduct this research.
The Automated e-Lung CT Algorithm is More Prognostic than Lung Function in Patients with Non-IPF Fibrotic ILD; A Validation Study
Data from the OISC Data Repository was used to conduct this research.
Novel e-Lung CT Biomarkers Combine to Provide Higher Prognostic Discrimination than FVC in Patients with Non-IPF Fibrotic Interstitial Lung Disesase
Data from the OSIC Data Repository was used to conduct this research.
Deep Learning-based Quantification of Traction Bronchiectasis Severity for Predicting Outcome in Idiopathic Pulmonary Fibrosis
OSIC is mentioned in this research.
Longitudinal changes in CT Quantified Pulmonary Artery Volume and Interstitial Abnormalities Correlate with Pulmonary Function Decline in IPF Patients
Data from the OSIC Data Repository was used to conduct research.
Shaping the Future in Rare Lung Diseases: From Imaging to Patient Management
OSIC is mentioned in this research.
Surface Projection of CT Reconstructed Lung Volume for Regional Lung Mechanics Estimation: A Preliminary Analysis
Data from the OSIC Data Repository was used to conduct this research.
Computer-Aided Pulmonary Fibrosis Detection Leveraging an Advanced Artificial Intelligence Triage and Notification Software
Data from the OSIC Data Repository was used to conduct this research.
Segmentation of Cardiac Tissue in CT for Coronary Artery Disease Screening
Data from the OSIC Data Repository was used to conduct this research. READ MORE ON UNIVERSIDADE DO PORTO
