Enrichment of lung cancer computed tomography collections with AI-derived annotations
Abstract Public imaging datasets are critical for the development and evaluation of automated tools in cancer imaging. Unfortunately, many do not include annotations or image-derived features, complicating downstream analysis. Artificial intelligence-based annotation tools have been shown to achieve...
Main Authors: | Deepa Krishnaswamy, Dennis Bontempi, Vamsi Krishna Thiriveedhi, Davide Punzo, David Clunie, Christopher P. Bridge, Hugo J. W. L. Aerts, Ron Kikinis, Andrey Fedorov |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2024-01-01
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Series: | Scientific Data |
Online Access: | https://doi.org/10.1038/s41597-023-02864-y |
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