Get Started with Radiomics

Radiomics is a technique in medical imaging that computes a large number of quantitative features from medical images. These features quantify characteristics related to the shape, intensity, and texture of a region of interest in a medical image, reducing dependence on subjective interpretation of medical images for clinical workflows. Further, radiomics can capture characteristics that are not visible. You can use the same set of radiomics features for any medical imaging modality and for multiple applications, such as studying associations between medical imaging features and patient biology and predicting clinical outcomes from medical images, which makes radiomics a versatile technique in medical imaging.

Standardization of radiomics features ensures reproducibility and validation of radiomics studies. The image biomarker standardisation initiative (IBSI) provides standardized nomenclature and definitions for radiomics features, a standard procedure for medical image preprocessing, and reporting guidelines, among other standardization tools.

Typical Workflow of Radiomics Application

Typical radiomics workflow

The typical workflow of a radiomics application involves these steps.

Import Medical Image into Workspace

Import the medical image into the workspace as a medicalVolume object. You can compute radiomics features from medical images of any modality, such as MRI, CT, or ultrasound. For more information, see Medical Imaging Modalities.

Preprocess Medical Image

Clean the acquired medical image using preprocessing techniques such as background removal, denoising, registration, augmentation, and intensity normalization. For more information, see Medical Image Preprocessing and Medical Image Registration.

Identify Region of Interest (ROI)

If you have already identified the ROI, import the mask of the ROI as a medicalVolume object. If you have not identified the ROI, segment the medical image to identify the region of interest. Medical Imaging Toolbox™ provides the Medical Image Labeler app and various functions for medical image segmentation. For more information, see Analysis and Applications.

Preprocess Medical Image for Radiomics

Use the radiomics object to preprocess the medical image as required by IBSI standards. Preprocessing for radiomics involves resampling, resegmentation, and discretization.

Radiomics Feature Computation

Use the shapeFeatures, intensityFeatures, and textureFeatures functions of the radiomics object to compute radiomics features related to the shape, intensity, and texture of the region of interest, respectively.

Postprocessing

You can apply statistical methods to the computed radiomics features to identify associations between medical imaging features and patient biology, or apply machine learning or deep learning models to predict clinical outcomes. For an example of clinical prediction using radiomics, see Classify Breast Tumors from Ultrasound Images Using Radiomics Features.