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 preliminary version of a reference manual on the use of convolutional image filters in radiomics. 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 have been found to be poorly reproducible. This reference manual forms the basis of ongoing work on standardising convolutional filters in radiomics, and will be updated as this work progresses.
- Pub Date:
- June 2020
- Electrical Engineering and Systems Science - Image and Video Processing;
- Computer Science - Computer Vision and Pattern Recognition;
- 68U10 (Primary) 68T45 (Secondary);
- 61 pages. For additional information see https://theibsi.github.io/ Changes in v4: * See document. Changes in v3: * Clarified how to scale Laplacian-of-Gaussian filter kernels. * Added 2D filter tests. Changes in v2: * Clarified how to reach rotational invariance for convolutional filtering. * Reworked description of Simoncelli filter. * Added intended filter dimensionality as a test parameter