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Validation of A Method to Compensate Multicenter Effects Affecting CT Radiomics

Radiology, 2019-04, Vol.291 (1), p.53-59

2019

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LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characterization of Tumor Heterogeneity

Cancer research (Chicago, Ill.), 2018-08, Vol.78 (16), p.4786-4789

2018

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Tumor Texture Analysis in PET: Where Do We Stand?

Journal of Nuclear Medicine, 2015-11, Vol.56 (11), p.1642-1644

2015

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Understanding Changes in Tumor Texture Indices in PET: A Comparison Between Visual Assessment and Index Values in Simulated and Patient Data

Journal of Nuclear Medicine, 2017-03, Vol.58 (3), p.387-392

2017

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A Postreconstruction Harmonization Method for Multicenter Radiomic Studies in PET

Journal of Nuclear Medicine, 2018-08, Vol.59 (8), p.1321-1328

2018

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A Guide to ComBat Harmonization of Imaging Biomarkers in Multicenter Studies

Journal of Nuclear Medicine, 2022-02, Vol.63 (2), p.172-179

2022

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18F-FDG PET-Derived Textural Indices Reflect Tissue-Specific Uptake Pattern in Non-Small Cell Lung Cancer

PloS one, 2015-12, Vol.10 (12), p.e0145063-e0145063

2015

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How can we combat multicenter variability in MR radiomics? Validation of a correction procedure

European radiology, 2021-04, Vol.31 (4), p.2272-2280

2021

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CheckList for EvaluAtion of Radiomics research (CLEAR): a step-by-step reporting guideline for authors and reviewers endorsed by ESR and EuSoMII

Insights into imaging, 2023-05, Vol.14 (1), p.75-13, Article 75

2023

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Comment on Ibrahim et al. The Effects of In-Plane Spatial Resolution on CT-Based Radiomic Features’ Stability with and without ComBat Harmonization. Cancers 2021, 13, 1848

Cancers, 2021-06, Vol.13 (12), p.3037

2021

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Relationship between tumor heterogeneity measured on FDG-PET/CT and pathological prognostic factors in invasive breast cancer

PloS one, 2014-04, Vol.9 (4), p.e94017

2014

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Inter-observer and segmentation method variability of textural analysis in pre-therapeutic FDG PET/CT in head and neck cancer

PloS one, 2019-03, Vol.14 (3), p.e0214299-e0214299

2019

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Prognostic value of textural indices extracted from pretherapeutic 18‐F FDG‐PET/CT in head and neck squamous cell carcinoma

Head & neck, 2019-02, Vol.41 (2), p.495-502

2019

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Correction for Magnetic Field Inhomogeneities and Normalization of Voxel Values Are Needed to Better Reveal the Potential of MR Radiomic Features in Lung Cancer

Frontiers in oncology, 2020-01, Vol.10, p.43-43

2020

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In Regard to Mattonen et al

International journal of radiation oncology, biology, physics, 2016-08, Vol.95 (5), p.1544-1545

2016

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The Dark Side of Radiomics: On the Paramount Importance of Publishing Negative Results

Journal of Nuclear Medicine, 2019-11, Vol.60 (11), p.1543-1544

2019

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Multiscale Texture Analysis: From 18F-FDG PET Images to Histologic Images

The Journal of nuclear medicine (1978), 2016-11, Vol.57 (11), p.1823-1828

2016

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The T.R.U.E. Checklist for Identifying Impactful Artificial Intelligence–Based Findings in Nuclear Medicine: Is It True? Is It Reproducible? Is It Useful? Is It Explainable?

Journal of Nuclear Medicine, 2021-06, Vol.62 (6), p.752-754

2021

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Tumor texture analysis in 18F-FDG PET: relationships between texture parameters, histogram indices, standardized uptake values, metabolic volumes, and total lesion glycolysis

The Journal of nuclear medicine (1978), 2014-03, Vol.55 (3), p.414-422

2014

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The T.R.U.E. checklist for identifying impactful AI-based findings in nuclear medicine: is it True? Is it Reproducible? Is it Useful? Is it Explainable?

The Journal of nuclear medicine (1978), 2021-03

2021

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The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping

Radiology, 2020-05, Vol.295 (2), p.328-338

2020

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Radiomics in Nuclear Medicine Applied to Radiation Therapy: Methods, Pitfalls, and Challenges

International journal of radiation oncology, biology, physics, 2018-11, Vol.102 (4), p.1117-1142

2018

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Radiomics in PET Imaging:: A Practical Guide for Newcomers

PET clinics, 2021-10, Vol.16 (4), p.597-612

2021

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Development and validation of a radiomic model for the diagnosis of dopaminergic denervation on [18F]FDOPA PET/CT

European journal of nuclear medicine and molecular imaging, 2022-09, Vol.49 (11), p.3787-3796

2022

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RadShap: An Explanation Tool for Highlighting the Contributions of Multiple Regions of Interest to the Prediction of Radiomic Models

Journal of Nuclear Medicine, 2024-08, Vol.65 (8), p.1307-1312

2024

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Validation of A Method to Compensate Multicenter Effects Affecting CT Radiomics

LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characterization of Tumor Heterogeneity

Tumor Texture Analysis in PET: Where Do We Stand?

Understanding Changes in Tumor Texture Indices in PET: A Comparison Between Visual Assessment and Index Values in Simulated and Patient Data

A Postreconstruction Harmonization Method for Multicenter Radiomic Studies in PET

A Guide to ComBat Harmonization of Imaging Biomarkers in Multicenter Studies

18F-FDG PET-Derived Textural Indices Reflect Tissue-Specific Uptake Pattern in Non-Small Cell Lung Cancer

How can we combat multicenter variability in MR radiomics? Validation of a correction procedure

CheckList for EvaluAtion of Radiomics research (CLEAR): a step-by-step reporting guideline for authors and reviewers endorsed by ESR and EuSoMII

Comment on Ibrahim et al. The Effects of In-Plane Spatial Resolution on CT-Based Radiomic Features’ Stability with and without ComBat Harmonization. Cancers 2021, 13, 1848

Relationship between tumor heterogeneity measured on FDG-PET/CT and pathological prognostic factors in invasive breast cancer

Inter-observer and segmentation method variability of textural analysis in pre-therapeutic FDG PET/CT in head and neck cancer

Prognostic value of textural indices extracted from pretherapeutic 18‐F FDG‐PET/CT in head and neck squamous cell carcinoma

Correction for Magnetic Field Inhomogeneities and Normalization of Voxel Values Are Needed to Better Reveal the Potential of MR Radiomic Features in Lung Cancer

In Regard to Mattonen et al

The Dark Side of Radiomics: On the Paramount Importance of Publishing Negative Results

Multiscale Texture Analysis: From 18F-FDG PET Images to Histologic Images

The T.R.U.E. Checklist for Identifying Impactful Artificial Intelligence–Based Findings in Nuclear Medicine: Is It True? Is It Reproducible? Is It Useful? Is It Explainable?

Tumor texture analysis in 18F-FDG PET: relationships between texture parameters, histogram indices, standardized uptake values, metabolic volumes, and total lesion glycolysis

The T.R.U.E. checklist for identifying impactful AI-based findings in nuclear medicine: is it True? Is it Reproducible? Is it Useful? Is it Explainable?

The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping

Radiomics in Nuclear Medicine Applied to Radiation Therapy: Methods, Pitfalls, and Challenges

Radiomics in PET Imaging:: A Practical Guide for Newcomers

Development and validation of a radiomic model for the diagnosis of dopaminergic denervation on [18F]FDOPA PET/CT

RadShap: An Explanation Tool for Highlighting the Contributions of Multiple Regions of Interest to the Prediction of Radiomic Models

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