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Congress: ECR25
Poster Number: C-12773
Type: Poster: EPOS Radiologist (scientific)
Authorblock: K. Bartnik1, T. Bartczak2, M. Krzyziński2, K. Korzeniowski1, K. J. Lamparski1, T. Wróblewski2, K. Mech2, M. M. Januszewicz1, P. Biecek2; 1Warszawa/PL, 2Warsaw/PL
Disclosures:
Krzysztof Bartnik: Grant Recipient: Integra WUM-PW (No. 1W12/ INTEGRA.1.6/N/23)
Tomasz Bartczak: Nothing to disclose
Mateusz Krzyziński: Nothing to disclose
Krzysztof Korzeniowski: Nothing to disclose
Krzysztof Jacek Lamparski: Nothing to disclose
Tadeusz Wróblewski: Nothing to disclose
Katarzyna Mech: Nothing to disclose
Magdalena Maria Januszewicz: Nothing to disclose
Przemysław Biecek: Nothing to disclose
Keywords: Artificial Intelligence, Liver, Oncology, CT, CT-Quantitative, Chemoembolisation, Outcomes analysis, Cancer, Cirrhosis
Conclusion

Our dataset significantly expands the available annotated data, complementing a recently published TACE dataset. Notably, it includes patients with multiple HCC lesions, rather than being limited to single tumors. This dataset includes comprehensive clinical data, pre-TACE CT imaging, segmentation masks and critical outcome measures. It is a valuable resource for enhancing AI-based research in radiology, aimed at improving outcomes for HCC patients.