Corpus ID: 219559156

Standardised convolutional filtering for radiomics

@article{Depeursinge2020StandardisedCF,
  title={Standardised convolutional filtering for radiomics},
  author={Adrien Depeursinge and Vincent Andrearczyk and Philip Whybra and Joost van Griethuysen and Henning M{\"u}ller and Roger Schaer and Martin Valli{\`e}res and Alex Zwanenburg},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.05470}
}
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… Expand
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References

SHOWING 1-10 OF 71 REFERENCES
3D Steerable Wavelets in Practice
TLDR
A systematic and practical design for steerable wavelet frames in 3D and a new inverse-problem formalism along with an optimization algorithm for reconstructing 3D images from a sparse set of wavelet-domain edges are proposed. Expand
Fundamentals of Texture Processing for Biomedical Image Analysis: A General Definition and Problem Formulation
TLDR
This chapter provides an overview of the foundations of texture processing for biomedical image analysis and proposes a general problem formulation to translate 2D and 3D textured patterns from biomedical images to visually and biologically relevant measurements. Expand
Local Rotation Invariance in 3D CNNs
TLDR
Several methods to obtain LRI CNNs with directional sensitivity are proposed and compared, showing the importance of LRI image analysis while resulting in a drastic reduction of trainable parameters, outperforming standard 3D CNNs trained with rotational data augmentation. Expand
The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping.
TLDR
A set of 169 radiomics features was standardized, which enabled verification and calibration of different radiomics software and could be excellently reproduced. Expand
Exploring local rotation invariance in 3D CNNs with steerable filters
TLDR
The results show the importance of LRI in CNNs and the need for a fine rotation sampling and a drastic reduction of trainable parameters and of convolution operations, as well as avoiding approximations due to interpolation of rotated kernels. Expand
Pulmonary nodule detection in CT scans with equivariant CNNs
TLDR
3D CNNs with group convolutions (3D G-CNNs) were applied to the problem of false positive reduction for pulmonary nodule detection in CT scans, and proved to be substantially more effective in terms of accuracy, sensitivity to malignant nodules, and speed of convergence compared to a strong and comparable baseline architecture. Expand
PyWavelets: A Python package for wavelet analysis
TLDR
This poster presents a probabilistic procedure to characterize the response of the immune system to x-ray diffraction during the treatment of central giant cell granuloma. Expand
Radiomics in nuclear medicine: robustness
  • reproducibility, standardization, and how to avoid data analysis traps and replication crisis. Eur. J. Nucl. Med. Mol. Imaging, 46(13):2638–2655
  • 2019
Radiomics in nuclear medicine: robustness, reproducibility, standardization, and how to avoid data analysis traps and replication crisis
  • A. Zwanenburg
  • Medicine, Computer Science
  • European Journal of Nuclear Medicine and Molecular Imaging
  • 2019
TLDR
A meta-analysis to investigate reproducibility of radiomics biomarkers in PET imaging and to obtain quantitative information regarding their sensitivity to variations in various imaging and radiomics-related factors as well as their inherent sensitivity is performed. Expand
and A
  • O’Leary. Pywavelets: A python package for wavelet analysis. Journal of Open Source Software, 4(36):1237
  • 2019
...
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4
5
...