Corpus ID: 219559156

Standardised convolutional filtering for radiomics

  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},
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
Definition and validation of a radiomics signature for loco-regional tumour control in patients with locally advanced head and neck squamous cell carcinoma
A CT-based radiomics signature for the prognosis of loco-regional tumour control (LRC) in patients with locally advanced head and neck squamous cell carcinoma treated by primary radiochemotherapy (RCTx) based on retrospective data from 6 partner sites of the DKTK-ROG is developed and validated. Expand
Enhancement of Radiosurgical Treatment Outcome Prediction Using MRI Radiomics in Patients with Non-Small Cell Lung Cancer Brain Metastases
  • Chien-Yi Liao, Cheng-Chia Lee, +6 authors Chia-Feng Lu
  • Medicine
  • Cancers
  • 2021
It is concluded that the identified radiomic features could provide valuable additional information to enhance the prediction of BM responses after GKRS, and an outcome prediction model based on radiomics combined with clinical features may guide therapy in these patients. Expand
Positron Emission Tomography-Based Short-Term Efficacy Evaluation and Prediction in Patients With Non-Small Cell Lung Cancer Treated With Hypo-Fractionated Radiotherapy
Positron emission tomography-based local objective response rate was significantly higher than that based on computed tomography, and the radiomics nomogram could be an important technique for the prediction of short-term efficacy, which might enable an improved and precise treatment. Expand
Prognostic Assessment in High-Grade Soft-Tissue Sarcoma Patients: A Comparison of Semantic Image Analysis and Radiomics
The performance of predictions of patients’ survival based on semantic features extracted by radiologists with a “radiomic” approach was compared and T2FS and T1FSGd-based radiomic models outperformed semantic imaging features for prognostic assessment. Expand
Quantitative CT radiomics-based models for prediction of haematoma expansion and poor functional outcome in primary intracerebral haemorrhage
Performance of radiomics-based features was boosted by incorporating clinical factors, with time from onset to scan and age being the most important contributors for haematoma expansion and poor functional outcome prediction, respectively. Expand
Robustness of magnetic resonance radiomic features to pixel size resampling and interpolation in patients with cervical cancer
Most MR radiomic features in patients with cervical cancer were robust after pixel size resampling and interpolation following the feature standardization process, and although most first-order, shape, and texture features showed good robustness, GLSZM small-area emphasis-related features and NGTDM strength were sensitive to variations in pixel size and slice thickness. Expand
The importance of feature aggregation in radiomics: a head and neck cancer study
It is shown that classical aggregation methods are not optimal in case of heterogeneous tumors, and the BoVW model is a better alternative to extract consistent features in the presence of lesions composed ofheterogeneous tissue. Expand


3D Steerable Wavelets in Practice
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
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
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.
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
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
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
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
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