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Image . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Image . 2024
License: CC BY
Data sources: Datacite
ZENODO
Image . 2024
License: CC BY
Data sources: Datacite
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CT dataset for "Integrated multiomics signatures to optimize the accurate diagnosis of lung cancer" Part-I

Authors: Zhao, Mengmeng; She, Yunlang;

CT dataset for "Integrated multiomics signatures to optimize the accurate diagnosis of lung cancer" Part-I

Abstract

To develop and validate a radiomics-based method for lung cancer detection, chest CT images of patients with pulmonary nodules from clinical 5 centers were collected. Due to size limit of zenodo.org, we split the whole dataset into 2 parts, and this is the Part 1. We hope this large-scale dataset could facilitate both clinical research for automatic lung cancer detection and diagnoses, and engineering research for 3D detection, segmentation and classification. This dataset is a research effort of thousands of hours by experienced thoracic surgeons, and radiologists. We kindly ask you to respect our effort by appropriate citation and keeping data license.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Related to Research communities
Cancer Research