-
Notifications
You must be signed in to change notification settings - Fork 104
Radiomics
Radiomics involves reducing the image within the region of interest (anaotmical structure) to scalar features. This typically involves accumulating contributions from all the voxels within the region of interest; for example the mean of intensities from all the voxels. The radiomics features can be calculated for the original or the texture (or pre-processed) images.
- First order (intensity)
- Peak and valley
- Shape
- Intensity Volume Histogram (IVH)
- Higher order (texture)
Batch calculate Global Radiomics features: This is an example to calculate global radiomics for a cohort of patients. It assumes that the anatomical structure is consistently named across the entire cohort.
Wrapper function for radiomics calculation: This is an example to demonstrate using the calcGlobalRadiomicsFeatures wrapper function to extract radiomics features.
Obtain scan values within an ROI for the patient cohort: This is an example to obtain the scan values from each and every voxel within the region of interest for the cohort of patients. This can be useful to determine the optimal number of discretization levels required for feature calculation.
Feature calculation used to generate various radiomics signatures is provided. For example, the following code computes the features used in Aerts et al's radiomics signature:
% Structure index
structNum = 1;
% Access the planC object
global planC
% Calculate the signature features
featureS = getNcomms5006Feature(structNum,planC)The radiomics test suite tests CERR's radiomics feature calculation with open-source software ITK. Sample scripts for comparison of radiomics calculations between CERR and Pyradiomics are also available. Additionally, test script for comparing CERR's radiomics implementation against IBSI benchmarks is provided.
Apte AP, Iyer A, Crispin-Ortuzar M, Pandya R, V.van Dijk L, Spezi E, Thor M, Um H, Veeraraghavan H, Oh JH, Shukla-Dave A, Deasy JO (2018). Technical Note: Extension of CERR for computational radiomics: a comprehensive MATLAB platform for reproducible radiomics research, Med. Phys., 45 (8), pp. 3713–3720, August 2018. PMID: 29896896