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Cloud-based Liquid-biopsy and Radiomics Platform for the Cancer Research Data Commons

Principal Investigator
Name
Chun-Chi Liu
Degrees
Ph.D.
Institution
EarlyDiagnostics
Position Title
Chief Computing Officer
Email
About this CDAS Project
Study
NLST (Learn more about this study)
Project ID
NLST-1323
Initial CDAS Request Approval
Sep 19, 2024
Title
Cloud-based Liquid-biopsy and Radiomics Platform for the Cancer Research Data Commons
Summary
Radiomics or imaging data analysis, as a counterpart to multi-omics data analysis, provide structural and functional details of tumors in parallel with the molecular features extracted from multi-omics data. Integrative analyses of multimodal data can uncover complex mechanisms of cancer and provide more reliable predictions. We will implement functions for radiomics analysis of the chest/lung CT scans data analysis. CT scan data are the most common type of non-invasive lung cancer diagnosis/prognosis data. We will implement analysis tools to gain insights from the imaging data, help uncover the underlying mechanisms of disease conditions and facilitate better decision-making.
Aims

We will conduct the following aims:
(1) Implement tools to access, query, and visualize imaging data through web-based interfaces. We will implement tools to: i) access and share image information from user-specified collections, cases, studies, or series; ii) query images and annotations by their attributes. The querying can be performed in a user-friendly interface or with SQL language; iii) visualize CT images and annotations.

(2) Implement image processing module to support image normalization and segmentation for machine learning. The module will consist of the following automated processing steps: i) Image normalization; ii) Lung segmentation; and iii) Nodule detection and segmentation.

Collaborators

William Hsu, UCLA