Standardised convolutional filtering for radiomics
This work is incremental, providing standardized guidelines to improve reproducibility for researchers in radiomics and medical imaging.
The paper addresses the poor reproducibility of features derived from convolutional filter response maps in radiomics by presenting a complete reference manual that standardizes definitions, parameters, reporting, and verification tests for convolutional filters. This effort builds on the Image Biomarker Standardisation Initiative to enhance consistency in quantitative image analysis.
The Image Biomarker Standardisation Initiative (IBSI) aims to improve reproducibility of radiomics studies by standardising the computational process of extracting image biomarkers (features) from images. We have previously established reference values for 169 commonly used features, created a standard radiomics image processing scheme, and developed reporting guidelines for radiomic studies. However, several aspects are not standardised. Here we present a complete version of a reference manual on the use of convolutional filters in radiomics and quantitative image analysis. Filters, such as wavelets or Laplacian of Gaussian filters, play an important part in emphasising specific image characteristics such as edges and blobs. Features derived from filter response maps were found to be poorly reproducible. This reference manual provides definitions for convolutional filters, parameters that should be reported, reference feature values, and tests to verify software compliance with the reference standard.