Develop generative AI models to enhance lung image processing for improved downstream clinical analysis
Principal Investigator
Name
kibrom girum
Degrees
Ph.D.
Institution
Institut Curie
Position Title
Research engineer
Email
About this CDAS Project
Study
NLST
(Learn more about this study)
Project ID
NLST-1164
Initial CDAS Request Approval
Dec 4, 2023
Title
Develop generative AI models to enhance lung image processing for improved downstream clinical analysis
Summary
We aim to investigate and develop generic generative artificial intelligence (AI) models to increase the data size.
It will improve the performance of other downstream medical image processing and thereby enhance the downstream clinical analysis, particularly to solve the current bottleneck of deep learning methods in adapting to different clinical settings or different data centers.
It will improve the performance of other downstream medical image processing and thereby enhance the downstream clinical analysis, particularly to solve the current bottleneck of deep learning methods in adapting to different clinical settings or different data centers.
Aims
- Investigate generative AI models
- Develop generative AI models that synthesizes lung medical images
- Improve medical image processing tasks, such as segmentation
- Improve clinical analysis
Collaborators
The project will be conducted under institut Curie for academic research.