Lung disease detection and measuring algorithms on chest X ray images.
Principal Investigator
Name
Joseph Chui
Degrees
MSc
Institution
Ferrum Health, Inc.
Position Title
Machine Vision Engineer
Email
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCO-491
Initial CDAS Request Approval
Jul 11, 2019
Title
Lung disease detection and measuring algorithms on chest X ray images.
Summary
Our algorithms use chest X ray images, diagnosis and patient demographics to train and validate inference models to:
Detect lung nodules and other lung/chest abnormalities, such as Granuloma and cardiac abnormalities, and measure their properties and characteristics.
It is important for our algorithms to train and validate the models, not only with data from patients of cancer or other abnormalities, but also with data from patients of negative diagnoses. The amount of data of negative findings in PLCO can become very valuable to the proposed project.
Our proposed project aims to train and validate statistical models using PLCO data as well as other datasets to improve the inference quality of the models.
With our granted access to the CT images of NLST, we are intending to investigate the inferring performances from models based on different imaging modalities.
Detect lung nodules and other lung/chest abnormalities, such as Granuloma and cardiac abnormalities, and measure their properties and characteristics.
It is important for our algorithms to train and validate the models, not only with data from patients of cancer or other abnormalities, but also with data from patients of negative diagnoses. The amount of data of negative findings in PLCO can become very valuable to the proposed project.
Our proposed project aims to train and validate statistical models using PLCO data as well as other datasets to improve the inference quality of the models.
With our granted access to the CT images of NLST, we are intending to investigate the inferring performances from models based on different imaging modalities.
Aims
Aim 1: Improving the quality of the inference models by including PLCO data in model training, and to validate the models with PLCO data held out from the training.
Aim 2: Assessing correlations of inference results between models using CT images and models using X Ray images.
Collaborators
Ferrum Health