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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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TCIA/TGCA-LIHC portal venous phase CT-scans for cirrhosis classification

Authors: Emma Sarfati; Alexandre Bône; Marc-Michel Rohé; Pietro Gori; Isabelle Bloch;

TCIA/TGCA-LIHC portal venous phase CT-scans for cirrhosis classification

Abstract

These are the scans provided by The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) data collection, published by The Cancer Imaging Archive here and used in our MICCAI 2023 paper. You can find the GitHub of the paper here. All the data are submitted to TCIA data usage policy and must be strictly respected by future users. The selected scans are in portal venous phase, which is the phase that is clinically used to identify cirrhosis. In this list, you will find all the patients available in the TCGA-LIHC database, regardless of the availability of the annotations or the duplicated patients at different dates. In the dataframe provided in the Git repo, you will find the dataframe with one scan per patient (only at the first date), and with the Ishak score for each patient provided in the TCIA/TGCA database, which are the exact ones that we used in the paper. The names of the scans in the dataframe match exactly the ones below, to ease reproducibility. The scans are already pre-processed and are the exact ones that we use in evaluation phase in the published paper.

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Keywords

Liver, Deep learning, Cirrhosis classification

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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.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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