Abstract
Quantitative Radiomic Phenotyping of Cervix Cancer
Highlights
Radiomics process comprises of following five major levels. i
A Combined (MATLAB and C++) code was generated using grey scale differentiations and contoured volumes to extract the features. These features can be used as predictive models for outcome prediction, distant metastasis risk analysis and genetics assessment, when a new patient data was given as input (Figure 2)
Radiomic features are better at predicting treatment response than conventional measures, such as tumor volume and diameter, and the maximum radiotracer uptake on positron emission tomography (PET) imaging.[19,20,21,22,23,24,25]
Summary
Radiomics process comprises of following five major levels. i. Correspondence: Surega Anbumani, HCG Bangalore Institute of Oncology, Bangalore, India, Email suregaanbumani@gmail.com Developing algorithms for image segmentation (Automatic/Semi automatic).
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