BPG is committed to discovery and dissemination of knowledge
Cited by in CrossRef
For: Stollmayer R, Budai BK, Tóth A, Kalina I, Hartmann E, Szoldán P, Bérczi V, Maurovich-Horvat P, Kaposi PN. Diagnosis of focal liver lesions with deep learning-based multi-channel analysis of hepatocyte-specific contrast-enhanced magnetic resonance imaging. World J Gastroenterol 2021; 27(35): 5978-5988 [PMID: 34629814 DOI: 10.3748/wjg.v27.i35.5978]
URL: https://www.wjgnet.com/1949-8470/full/v27/i35/5978.htm
Number Citing Articles
1
Jingwei Wei, Hanyu Jiang, Yu Zhou, Jie Tian, Felipe S. Furtado, Onofrio A. Catalano. Radiomics: A radiological evidence-based artificial intelligence technique to facilitate personalized precision medicine in hepatocellular carcinomaDigestive and Liver Disease 2023; 55(7): 833 doi: 10.1016/j.dld.2022.12.015
2
Pasquale Avella, Micaela Cappuccio, Teresa Cappuccio, Marco Rotondo, Daniela Fumarulo, Germano Guerra, Guido Sciaudone, Antonella Santone, Francesco Cammilleri, Paolo Bianco, Maria Chiara Brunese. Artificial Intelligence to Early Predict Liver Metastases in Patients with Colorectal Cancer: Current Status and Future ProspectivesLife 2023; 13(10): 2027 doi: 10.3390/life13102027
3
Zhen Wang, Jundong Yao, Xiang Jing, Kaiyan Li, ShiChun Lu, Hong Yang, Hong Ding, Kai Li, Wen Cheng, Guangzhi He, Tianan Jiang, Fangyi Liu, Jie Yu, Zhiyu Han, Zhigang Cheng, Shuilian Tan, Zhen Wang, Erpeng Qi, Shuo Wang, YiQiong Zhang, Lu Li, Xiaocong Dong, Ping Liang, Xiaoling Yu. A combined model based on radiomics features of Sonazoid contrast-enhanced ultrasound in the Kupffer phase for the diagnosis of well-differentiated hepatocellular carcinoma and atypical focal liver lesions: a prospective, multicenter studyAbdominal Radiology 2024;  doi: 10.1007/s00261-024-04253-4
4
Ke Wang, Yuehua Liu, Hongxin Chen, Wenjin Yu, Jiayin Zhou, Xiaoying Wang. Fully automating LI-RADS on MRI with deep learning-guided lesion segmentation, feature characterization, and score inferenceFrontiers in Oncology 2023; 13 doi: 10.3389/fonc.2023.1153241
5
Qiuxia Wei, Nengren Tan, Shiyu Xiong, Wanrong Luo, Haiying Xia, Baoming Luo. Deep Learning Methods in Medical Image-Based Hepatocellular Carcinoma Diagnosis: A Systematic Review and Meta-AnalysisCancers 2023; 15(23): 5701 doi: 10.3390/cancers15235701
6
Jia Guo, Dong Jiang, Yi Qian, Jiao Yu, Yi-Jun Gu, Yu-Qing Zhou, Hui-Ping Zhang. Differential diagnosis of different types of solid focal liver lesions using two-dimensional shear wave elastographyWorld Journal of Gastroenterology 2022; 28(32): 4716-4725 doi: 10.3748/wjg.v28.i32.4716
7
Alessandro Martinino, Mohammad Aloulou, Surobhi Chatterjee, Juan Pablo Scarano Pereira, Saurabh Singhal, Tapan Patel, Thomas Paul-Emile Kirchgesner, Salvatore Agnes, Salvatore Annunziata, Giorgio Treglia, Francesco Giovinazzo. Artificial Intelligence in the Diagnosis of Hepatocellular Carcinoma: A Systematic ReviewJournal of Clinical Medicine 2022; 11(21): 6368 doi: 10.3390/jcm11216368
8
Aladár David Rónaszéki, Ibolyka Dudás, Boglarka Zsély, Bettina Katalin Budai, Róbert Stollmayer, Oszkár Hahn, Barbara Csongrády, Byung-so Park, Pál Maurovich-Horvat, Gabriella Győri, Pal Novak Kaposi. Microvascular flow imaging to differentiate focal hepatic lesions: the spoke-wheel pattern as a specific sign of focal nodular hyperplasiaUltrasonography 2023; 42(1): 172 doi: 10.14366/usg.22028
9
Feifei Lu, Yao Meng, Xiaoting Song, Xiaotong Li, Zhuang Liu, Chunru Gu, Xiaojie Zheng, Yi Jing, Wei Cai, Kanokwan Pinyopornpanish, Andrea Mancuso, Fernando Gomes Romeiro, Nahum Méndez-Sánchez, Xingshun Qi. Artificial Intelligence in Liver Diseases: Recent AdvancesAdvances in Therapy 2024; 41(3): 967 doi: 10.1007/s12325-024-02781-5
10
Benjamin Koh, Pojsakorn Danpanichkul, Meng Wang, Darren Jun Hao Tan, Cheng Han Ng. Application of artificial intelligence in the diagnosis of hepatocellular carcinomaeGastroenterology 2023; 1(2): e100002 doi: 10.1136/egastro-2023-100002
11
Haoran Dai, Yuyao Xiao, Caixia Fu, Robert Grimm, Heinrich von Busch, Bram Stieltjes, Moon Hyung Choi, Zhoubing Xu, Guillaume Chabin, Chun Yang, Mengsu Zeng. Deep Learning–Based Approach for Identifying and Measuring Focal Liver Lesions on Contrast‐Enhanced MRIJournal of Magnetic Resonance Imaging 2024;  doi: 10.1002/jmri.29404
12
Róbert Stollmayer, Bettina Katalin Budai, Aladár Rónaszéki, Zita Zsombor, Ildikó Kalina, Erika Hartmann, Gábor Tóth, Péter Szoldán, Viktor Bérczi, Pál Maurovich-Horvat, Pál Novák Kaposi. Focal Liver Lesion MRI Feature Identification Using Efficientnet and MONAI: A Feasibility StudyCells 2022; 11(9): 1558 doi: 10.3390/cells11091558