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资源简介：
List of extracted radiomic features.
应用场景：
创建时间：
2018-08-31
相关数据集
DataSheet_1_Diagnostic Performance of 2D and 3D T2WI-Based Radiomics Features With Machine Learning Algorithms to Distinguish Solid Solitary Pulmonary Lesion.csv
ObjectiveTo evaluate the performance of 2D and 3D radiomics features with different machine learning approaches to classify SPLs based on magnetic resonance(MR) T2 weighted imaging (T2WI). Material an
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Additional file 4 of The preoperative prognostic value of the radiomics nomogram based on CT combined with machine learning in patients with intrahepatic cholangiocarcinoma
Additional file 4: Supplement Figure 1 and 2. Radiomics feature selection using a parametric method, the LASSO logistic regression.
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Additional file 22 of Applications of radiomics-based analysis pipeline for predicting epidermal growth factor receptor mutation status
Additional file 22. Results of radiomic feature selection by mutual information and Scale algorithm without center -scaling in PET images.
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PHE-SICH-CT-IDS
This publicly available dataset namely PHE-SICH-CT-IDS, which is constructed 120 CT scans of patients with SICH. PHE-SICH-CT-IDS contains 3,511 CT images of SICH occurring in the basal ganglia region,
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List of stable radiomic features not statistically different if extracted using one segment layer at a time or considering the whole tumour volume in CT images of the oesophagus.
In bold, common features among three cohorts considered that showed to be stable and dimensionality and contrast agent independent. GLCM, grey level co-occurrence matrix; GLRLM, grey level run length
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