WAW-TACE: A Hepatocellular Carcinoma Multiphase CT Dataset with Segmentations, Radiomics Features, and Clinical Data

The WAW-TACE dataset contains baseline multiphase abdominal CT images from 233 treatment-naive patients with hepatocellular carcinoma treated with transarterial chemoembolization and includes 377 handcrafted liver tumor masks, automated segmentations of multiple internal organs, extracted radiomics features, and corresponding extensive clinical data. The dataset can be accessed at https://zenodo.org/records/12741586 .

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Publication Details

Journal
Radiology Artificial Intelligence
Published
2024-10-23
DOI
https://doi.org/10.1148/ryai.240296
Citations
11
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
4.45

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article

WAW-TACE: A Hepatocellular Carcinoma Multiphase CT Dataset with Segmentations, Radiomics Features, and Clinical Data

Magdalena Januszewicz, Tomasz Bartczak, Krzysztof Korzeniowski, Mateusz Krzyziński et al.
11 citations
Radiology Artificial Intelligence
Radiomics and Machine Learning in Medical Imaging
4.45
article

WAW-TACE: A Hepatocellular Carcinoma Multiphase CT Dataset with Segmentations, Radiomics Features, and Clinical Data

Magdalena Januszewicz, Tomasz Bartczak, Krzysztof Korzeniowski, Mateusz Krzyziński, Mateusz Bartkowiak, Tadeusz Wróblewski, Przemysław Biecek, Krzysztof Bartnik, Krzysztof Lamparski, Katarzyna Mech, Eric Lam, Piotr Węgrzyn
article en
11 citations

Abstract

The WAW-TACE dataset contains baseline multiphase abdominal CT images from 233 treatment-naive patients with hepatocellular carcinoma treated with transarterial chemoembolization and includes 377 handcrafted liver tumor masks, automated segmentations of multiple internal organs, extracted radiomics features, and corresponding extensive clinical data. The dataset can be accessed at https://zenodo.org/records/12741586 .

Radiology Artificial IntelligenceVol. 6(6)
Medical University of Warsaw (PL)
Warszawski Uniwersytet Medyczny, Politechnika Warszawska, Uniwersytet Warszawski
Good health and well-being
Openalex Percentile: Top 5%
Radiomics and Machine Learning in Medical Imaging
4.45
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