Cancer Imaging

Papers
(The H4-Index of Cancer Imaging is 22. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-05-01 to 2024-05-01.)
ArticleCitations
How to develop a meaningful radiomic signature for clinical use in oncologic patients111
18F-FDG PET/CT based spleen to liver ratio associates with clinical outcome to ipilimumab in patients with metastatic melanoma47
Mass-forming pancreatitis versus pancreatic ductal adenocarcinoma: CT and MR imaging for differentiation43
Radiomics for glioblastoma survival analysis in pre-operative MRI: exploring feature robustness, class boundaries, and machine learning techniques38
What scans we will read: imaging instrumentation trends in clinical oncology35
A radiomics nomogram for the prediction of overall survival in patients with hepatocellular carcinoma after hepatectomy35
MRI-based radiomics models to assess prostate cancer, extracapsular extension and positive surgical margins33
Predicting microvascular invasion in hepatocellular carcinoma: a deep learning model validated across hospitals31
Early response assessment and prediction of overall survival after peptide receptor radionuclide therapy30
Pharmacokinetic parameters and radiomics model based on dynamic contrast enhanced MRI for the preoperative prediction of sentinel lymph node metastasis in breast cancer29
Robustness of magnetic resonance radiomic features to pixel size resampling and interpolation in patients with cervical cancer28
A CT-based radiomics nomogram for prediction of lung adenocarcinomas and granulomatous lesions in patient with solitary sub-centimeter solid nodules28
Intratumoral and peritumoral radiomics analysis for preoperative Lauren classification in gastric cancer28
Whole-body magnetic resonance imaging (WB-MRI) for cancer screening in asymptomatic subjects of the general population: review and recommendations28
The diagnostic performance of quantitative mapping in breast cancer patients: a preliminary study using synthetic MRI27
MRI features predict microvascular invasion in intrahepatic cholangiocarcinoma26
CT-based radiomics features in the prediction of thyroid cartilage invasion from laryngeal and hypopharyngeal squamous cell carcinoma25
Tumor stiffness measured by shear wave elastography correlates with tumor hypoxia as well as histologic biomarkers in breast cancer24
A CT-based radiomics nomogram for distinguishing between benign and malignant bone tumours24
Validation of 18F-FDG PET/MRI and diffusion-weighted MRI for estimating the extent of peritoneal carcinomatosis in ovarian and endometrial cancer -a pilot study23
Outcomes assessment in intrahepatic cholangiocarcinoma using qualitative and quantitative imaging features23
Radiomic signature based on CT imaging to distinguish invasive adenocarcinoma from minimally invasive adenocarcinoma in pure ground-glass nodules with pleural contact22
Diagnostic value of 18F-FDG PET/MRI for staging in patients with endometrial cancer22
Multi-view secondary input collaborative deep learning for lung nodule 3D segmentation22
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