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Congress: ECR25
Poster Number: C-11739
Type: Poster: EPOS Radiologist (scientific)
DOI: 10.26044/ecr2025/C-11739
Authorblock: X. Tang, F. Wu, S. Ye, J. Lu; Hangzhou/CN
Disclosures:
Xin Tang: Nothing to disclose
Fan Wu: Nothing to disclose
Shengli Ye: Nothing to disclose
Jinlan Lu: Nothing to disclose
Keywords: Artificial Intelligence, Liver, Lung, CT, PET-CT, PET-MR, Acceptance testing, Cancer
References

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[2] Wu F, Cao G, Lu J, Ye S, Tang X. Correlation between 18 F-FDG PET/CT metabolic parameters and microvascular invasion before liver transplantation in patients with hepatocellular carcinoma. Nucl Med Commun. 2024 Dec 1;45(12):1033-1038. doi: 10.1097/MNM.0000000000001897. Epub 2024 Sep 13. PMID: 39267532; PMCID: PMC11537472.

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[5] Kwak MS, Lee HH, Yang JM, Cha JM, Jeon JW, Yoon JY, et al. Deep Convolutional Neural Network-Based Lymph Node Metastasis Prediction for Colon Cancer Using Histopathological Images. Front Oncol 2021;10:619803.
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