Harmonization strategies in multicenter MRI-based radiomics
E Stamoulou, C Spanakis, GC Manikis, G Karanasiou… - Journal of …, 2022 - mdpi.com
Radiomics analysis is a powerful tool aiming to provide diagnostic and prognostic patient
information directly from images that are decoded into handcrafted features, comprising …
information directly from images that are decoded into handcrafted features, comprising …
Making radiomics more reproducible across scanner and imaging protocol variations: a review of harmonization methods
Radiomics converts medical images into mineable data via a high-throughput extraction of
quantitative features used for clinical decision support. However, these radiomic features are …
quantitative features used for clinical decision support. However, these radiomic features are …
Standardization of brain MR images across machines and protocols: bridging the gap for MRI-based radiomics
Radiomics relies on the extraction of a wide variety of quantitative image-based features to
provide decision support. Magnetic resonance imaging (MRI) contributes to the …
provide decision support. Magnetic resonance imaging (MRI) contributes to the …
The application of a workflow integrating the variable reproducibility and harmonizability of radiomic features on a phantom dataset
Radiomics–the high throughput extraction of quantitative features from medical images and
their correlation with clinical and biological endpoints-is the subject of active and extensive …
their correlation with clinical and biological endpoints-is the subject of active and extensive …
[HTML][HTML] AutoComBat: a generic method for harmonizing MRI-based radiomic features
The use of multicentric data is becoming essential for developing generalizable radiomic
signatures. In particular, Magnetic Resonance Imaging (MRI) data used in brain oncology …
signatures. In particular, Magnetic Resonance Imaging (MRI) data used in brain oncology …
Radiomics feature robustness as measured using an MRI phantom
Radiomics involves high-throughput extraction of large numbers of quantitative features from
medical images and analysis of these features to predict patients' outcome and support …
medical images and analysis of these features to predict patients' outcome and support …
Evaluation of conventional and deep learning based image harmonization methods in radiomics studies
Objective. To evaluate the impact of image harmonization on outcome prediction models
using radiomics. Approach. 234 patients from the Brain Tumor Image Segmentation …
using radiomics. Approach. 234 patients from the Brain Tumor Image Segmentation …
A transfer learning approach to facilitate ComBat-based harmonization of multicentre radiomic features in new datasets
Purpose To facilitate the demonstration of the prognostic value of radiomics, multicenter
radiomics studies are needed. Pooling radiomic features of such data in a statistical analysis …
radiomics studies are needed. Pooling radiomic features of such data in a statistical analysis …
How can we combat multicenter variability in MR radiomics? Validation of a correction procedure
Objective Test a practical realignment approach to compensate the technical variability of
MR radiomic features. Methods T1 phantom images acquired on 2 scanners, FLAIR and …
MR radiomic features. Methods T1 phantom images acquired on 2 scanners, FLAIR and …
A novel benchmarking approach to assess the agreement among radiomic tools
Background The translation of radiomic models into clinical practice is hindered by the
limited reproducibility of features across software and studies. Standardization is needed to …
limited reproducibility of features across software and studies. Standardization is needed to …