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Unsupervised Deep Learning Detection of Lung Cancer Nodules

Principal Investigator
Name
Ouwen Huang
Degrees
M.D., Ph.D., Candidate
Institution
Gradient Health
Position Title
Chief Scientific Officer
Email
About this CDAS Project
Study
NLST (Learn more about this study)
Project ID
NLST-758
Initial CDAS Request Approval
Feb 8, 2021
Title
Unsupervised Deep Learning Detection of Lung Cancer Nodules
Summary
Deep learning has been shown to successfully detect lung nodules in CT scans and is projected to be used in automated screening pipelines. However, one challenge is the requirement for data labels which are time consuming and costly to obtain. Such algorithms would allow more efficient detection model improvements. We propose using unsupervised learning methods within a human-in-the-loop pipeline to assist in collecting high quality labels that can be used to continuously improve detection models.
Aims

1. Develop unsupervised methods to improve data labeling processes
2. Assess automated cancer detection performance in relation to the number of labelled cases

Collaborators

Gradient Health Inc.