Predicting malignant nodules from screening CTs
Determine if quantitative analyses (“radiomics”) of low dose CT lung cancer screening images at baseline can predict subsequent emergence of cancer.
Learn moreEveryone knows 3D Slicer, a powereful medic-images clinical, biomedical and reaserch tool. But we focus on Drawing ROI with Segmentation and Features Extracting with Radiomics module.
Learn moreRadiomics can provide powerful tools for cancer diagnosis and prognosis.
Learn morePowerful & popular tools for radiomics feature extraction and analysis.
Learn moreThere are some cases and reaserch about Radiomics, which providing a demonstration of the clinical potential of radiomics as a powerful to for personalized therapy.
Determine if quantitative analyses (“radiomics”) of low dose CT lung cancer screening images at baseline can predict subsequent emergence of cancer.
Learn moreAssess the stability and reproducibility of CT radiomic features extracted from the peritumoral regions of lung lesions.
Learn moreReview radiomic application areas and technical issues, as well as proper practices for the designs of radiomic studies.
Learn moreEvaluates CT radiomic features for their capability to predict distant metastasis for lung adenocarcinoma patients.
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