OSICild.org • Open Source Imaging Consortium

Prognostic Model for Idiopathic Pulmonary Fibrosis Using Context-Aware Sequential-Parallel Hybrid Transformer and Enriched Clinical Information

3/1/2025

OSIC is mentioned in this research.

ScreenDx, an artificial intelligence-based algorithm for the incidental detection of pulmonary fibrosis

2/26/2025

Data from the OSIC Data Repository was used to conduct this research.

Open-Source Manually Annotated Vocal Tract Database for Automatic Segmentation from 3D MRI Using Deep Learning: Benchmarking 2D and 3D Convolutional and Transformer Networks

1/8/2025

Data from the OSIC Data Repository was used to conduct this research.

RealDiffFusionNet: Neural Controlled Differential Equation Informed Multi-Head Attention Fusion Networks for Disease Progression Modeling Using Real-World Data

1/2/2025

Data from the OSIC Data Repository was used to conduct this research.

CT Quantification of Interstitial Lung Abnormality and Interstitial Lung Disease: From Technical Challenges to Future Directio

1/1/2025

Data from the OSIC Data Repository was used to conduct this research.

Alpha-1 Trailblazers

11/18/2024

During Alpha-1 Awareness Month, OSIC founding member CSL Behring shares three inspiring stories from the Alpha-1 Antitrypsin Deficiency community, one of which is a profile of OSIC’s research initiatives in this space.

World Orphan Drug Congress

10/24/2024

Executive Director Elizabeth Estes discussed OSIC’s progress in developing biomarkers for rare lung disease as a result of collaboration between academia, industry and philanthropy.

Vision Intelligence Assisted Lung Function Estimation Based on Transformer Encoder–Decoder Network With Invertible Modeling

10/22/2024

OSIC is mentioned in this research.

In Non-IPF Fibrosing ILD, E-Lung Biomarkers are Associated with the Future Development of Progressive Pulmonary Fibrosis Independent of UIP Status on CT Scan

10/8/2024

Data from the OSIC Data Repository was used to conduct this research.

Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge

10/1/2024

Data from the OSIC Data Repository was used to conduct this research.

Metric learning guided sinogram denoising for cone beam CT enhancement

10/1/2024

Data from the OSIC Data Repository was used to conduct this research.

Performance Evaluation and Validation of e-Lung in non-IPF fibrotic ILD

9/1/2024

Data from the OSIC Data Repository was used to conduct this research.

8th Annual IPF Summit

8/22/2024

Executive Director Elizabeth Estes shared insights on how robust clinical data curation, global normalization, and advanced data power can drive radical progress in drug development for fibrosing lung diseases.

Computed tomography machine learning classifier correlates with mortality in interstitial lung disease

7/1/2024

Data from the OSIC Data Repository was used to conduct this research.

Medical Image Segmentation using DUCK-Net

6/1/2024

Data from the OSIC Data Repository was used to conduct this research.

Utilization of Imaging and Clinical Data in Predicting Lung Capacity Progression in Patients with Fibrosis

6/1/2024

Data from the OSIC Data Repository was used to conduct this research.

Machine learning classifier is associated with mortality in interstitial lung disease: a retrospective validation study leveraging registry data

5/23/2024

Data from the OSIC Data Repository was used to conduct this research.

From pixels to prognosis: unlocking the potential of deep learning in fibrotic lung disease imaging analysis

5/23/2024

OSIC is mentioned in this research.

Multi-modal Machine Learning Classifier for Idiopathic Pulmonary Fibrosis Predicts Mortality in Interstitial Lung Diseases

5/21/2024

Data from the OSIC Data Repository was used to conduct this research.

ATS 2024 International Conference

5/21/2024

Dr. Kevin Brown and Dr. Simon Walsh discussed recent developments in machine learning algorithms using the OSIC Cloud Data Repository during this Industry Theater presentation.

Evaluating Radiomic-derived Features Across Different Image Convolution Kernels for Predicting IPF Patient Survival

5/20/2024

Data from the OSIC Data Repository was used to conduct this research.

Towards the adoption of quantitative computed tomography in the management of interstitial lung disease

4/17/2024

OSIC members discuss how quantitative CT software has huge potential to develop imaging biomarkers to improve the management of fibrosing ILDs, but optimizing their adoption will require technical and societal challenges to be addressed.

<<Previous

Prognostic Model for Idiopathic Pulmonary Fibrosis Using Context-Aware Sequential-Parallel Hybrid Transformer and Enriched Clinical Information

ScreenDx, an artificial intelligence-based algorithm for the incidental detection of pulmonary fibrosis

Open-Source Manually Annotated Vocal Tract Database for Automatic Segmentation from 3D MRI Using Deep Learning: Benchmarking 2D and 3D Convolutional and Transformer Networks

RealDiffFusionNet: Neural Controlled Differential Equation Informed Multi-Head Attention Fusion Networks for Disease Progression Modeling Using Real-World Data

CT Quantification of Interstitial Lung Abnormality and Interstitial Lung Disease: From Technical Challenges to Future Directio

Alpha-1 Trailblazers

World Orphan Drug Congress

Vision Intelligence Assisted Lung Function Estimation Based on Transformer Encoder–Decoder Network With Invertible Modeling

In Non-IPF Fibrosing ILD, E-Lung Biomarkers are Associated with the Future Development of Progressive Pulmonary Fibrosis Independent of UIP Status on CT Scan

Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge

Metric learning guided sinogram denoising for cone beam CT enhancement

Performance Evaluation and Validation of e-Lung in non-IPF fibrotic ILD

8th Annual IPF Summit

Computed tomography machine learning classifier correlates with mortality in interstitial lung disease

Medical Image Segmentation using DUCK-Net

Utilization of Imaging and Clinical Data in Predicting Lung Capacity Progression in Patients with Fibrosis

Machine learning classifier is associated with mortality in interstitial lung disease: a retrospective validation study leveraging registry data

From pixels to prognosis: unlocking the potential of deep learning in fibrotic lung disease imaging analysis

Multi-modal Machine Learning Classifier for Idiopathic Pulmonary Fibrosis Predicts Mortality in Interstitial Lung Diseases

ATS 2024 International Conference

Evaluating Radiomic-derived Features Across Different Image Convolution Kernels for Predicting IPF Patient Survival

Towards the adoption of quantitative computed tomography in the management of interstitial lung disease

A Machine Learning System to Indicate Diagnosis of Idiopathic Pulmonary Fibrosis Non-Invasively in Challenging Cases

Revolutionizing Pulmonary Diagnostics: A Narrative Review of Artificial Intelligence Applications in Lung Imaging

ASPPH 2024 Annual Meeting

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