BPG is committed to discovery and dissemination of knowledge
Cited by in CrossRef
For: Sim JZT, Hui TCH, Chuah TK, Low HM, Tan CH, Shelat VG. Efficacy of texture analysis of pre-operative magnetic resonance imaging in predicting microvascular invasion in hepatocellular carcinoma. World J Clin Oncol 2022; 13(11): 918-928 [PMID: 36483976 DOI: 10.5306/wjco.v13.i11.918]
URL: https://www.wjgnet.com/2218-4333/full/v13/i11/918.htm
Number Citing Articles
1
Valentina Brancato, Marco Cerrone, Nunzia Garbino, Marco Salvatore, Carlo Cavaliere. Current status of magnetic resonance imaging radiomics in hepatocellular carcinoma: A quantitative review with Radiomics Quality ScoreWorld Journal of Gastroenterology 2024; 30(4): 381-417 doi: 10.3748/wjg.v30.i4.381
2
Si-Ping Xiong, Chun-Hua Wang, Mei-fang Zhang, Xia Yang, Jing-Ping Yun, Li-Li Liu. A multi-parametric prognostic model based on clinicopathologic features: vessels encapsulating tumor clusters and hepatic plates predict overall survival in hepatocellular carcinoma patientsJournal of Translational Medicine 2024; 22(1) doi: 10.1186/s12967-024-05296-3
3
Hsien Min Low, Jeong Min Lee, Cher Heng Tan. Prognosis Prediction of Hepatocellular Carcinoma Based on Magnetic Resonance Imaging FeaturesKorean Journal of Radiology 2023; 24(7): 660 doi: 10.3348/kjr.2023.0168
4
Laura Jacqueline Jensen, Damon Kim, Thomas Elgeti, Ingo Günter Steffen, Lars-Arne Schaafs, Bernd Hamm, Sebastian Niko Nagel. The role of parametric feature maps to correct different volume of interest sizes: an in vivo liver MRI studyEuropean Radiology Experimental 2023; 7(1) doi: 10.1186/s41747-023-00362-9