Deep learning ultrasound radiomics nomogram for predicting Ki-67 expression in invasive breast cancerLU Lili, LI Lin, DU Huan, ZHANG Panpan, ZHU Yinhua, JIA Xiaohan, LI Yang1325-1332
Comparison of image quality of non-contrast MR pulmonary angiography with isotropyLI Ziyuan, BI Zhongxu, LI Wei, LIU Jia, ZHAO Kai, QIU Jianxing1333-1338
The feasibility and influencing factors of measuring the extracranial facial nerve in healthy individuals using ultra-high frequency ultrasoundZUO Yan, TANG Xinyi, ZHANG Jingyi, QIU Li1339-1343
3.0T MRI T2 mapping combined with diffusion tensor imaging can effectively evaluate type 2 diabetic peripheral neuropathyYANG Yulin, KOU Mengqi, TIAN Yiqun, GAO Yuting, LIU Yemei, YANG Lanying1344-1352
Ultrasound-derived fat fraction can quantitatively diagnose moderate to severe fatty liver:correlation with non-enhanced multislice helieal CT valuesXIE Xia, ZHANG Huabin, LUAN Haomei, WANG Lixue, LI Jie1353-1357
Deep learning-based super-resolution optimization enhances diffusion-weighted MRI quality for small hepatocellular carcinomaLIU Xuhong, ZHANG Qianying, DING Bijiao, HUANG Ying, HUANG Detian, HE Guifeng, DENG Na, HAN Xiaobing, LIN Yaping, LIU Nahong1358-1363
The value of DLIR algorithm in optimizing the image quality of low-kV head and neck CT angiographySHEN Li, REN Zhanli, PENG Hui, YU Yong, ZHANG Ming, YU Nan, YAN Yangyang1364-1368
Contrast-enhanced ultrasound features combined with spectral CT quantitative parameters can predict the WHO/ISUP grading of clear cell renal cell carcinomaQUAN Jiayu, JIA Chunmei, WEI Jianglong, ZHANG Xiao, DUAN Mujie1369-1376
Research on an MRI radiomics-based diagnostic model for differentiating ovarian Cystadenoma and cystadenocarcinomaTANG Yanan, LI Xiang, MA Yichuan1377-1384
Multimodal MRI and mammography radiomics for predicting axillary lymph node metastasis in breast cancerLIU Shengzhong, HUANG Cancan, ZHAO Li, ZHANG Ziqiu, LI Dechun1385-1391