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Insights Into Imaging|October 8, 2025
CT-based radiomics nomogram to predict response of advanced adenocarcinoma of esophagogastric junction to neoadjuvant chemotherapyChuan-Qinyuan Zhou, Yue-Su Wang, Wen-Han Liao, et al.
Insights Into Imaging|June 27, 2025
Advantages of BioMatrix respiratory gating in free-breathing three-dimensional magnetic resonance cholangiopancreatography: a prospective comparative studyQing Yang, Xueyi Ding, Qiuyang Guo, et al.
Insights Into Imaging|June 27, 2025
Incidental findings in female pelvis MRI performed for gynaecological malignanciesSilvia Bottazzi, Roberta V Ninkova, Luca Russo, et al.
Insights Into Imaging|June 27, 2025
A multi-view CNN model to predict resolving of new lung nodules on follow-up low-dose chest CTJingxuan Wang, Xiaowen Zhang, Wei Tang, et al.
Insights Into Imaging|July 3, 2025
Cross-validation of an artificial intelligence tool for fracture classification and localization on conventional radiography in Dutch populationHuibert C Ruitenbeek, Sahil Sahil, Aradhana Kumar, et al.
Insights Into Imaging|July 10, 2025
Objective assessment of diagnostic image quality in CT scans: what radiologists and researchers need to knowEva J I Hoeijmakers, Bibi Martens, Joachim E Wildberger, et al.
Insights Into Imaging|July 3, 2025
Interpretable and generalizable deep learning model for preoperative assessment of microvascular invasion and outcome in hepatocellular carcinoma based on MRI: a multicenter studyXue Dong, Xibin Jia, Wei Zhang, et al.
Insights Into Imaging|June 30, 2025
Thin-slice T2-weighted images and deep-learning-based super-resolution reconstruction: improved preoperative assessment of vascular invasion for pancreatic ductal adenocarcinomaXiaoqi Zhou, Yuxin Wu, Yanjin Qin, et al.
Insights Into Imaging|January 12, 2026
FRACTURE MRI: evaluation of imaging capability in hand tendon visualization using healthy volunteer MRIYukari Matsuzawa, Yusuke Matsuura, Kaoru Kitsukawa, et al.
Insights Into Imaging|December 22, 2025
Skull-stripping induces shortcut learning in MRI-based Alzheimer's disease classificationChristian Tinauer, Maximilian Sackl, Rudolf Stollberger, et al.
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