Harmonization strategies for multicenter radiomics investigations

Carrying out large multicenter studies is one of the key goals to be achieved towards a faster transfer of the radiomics approach in the clinical setting. This requires large-scale radiomics data analysis, hence the need for integrating radiomic features extracted from images acquired in different centers. This is challenging as radiomic features exhibit variable sensitivity to differences in scanner model, acquisition protocols and reconstruction settings, which is similar to the so-called ‘batch-effects’ in genomics studies. In this review we discuss existing methods to perform data integration with the aid of reducing the unwanted variation associated with batch effects. We also discuss the future potential role of deep learning methods in providing solutions for addressing radiomic multicentre studies.

• Publication year

  2020

• Venue

  Physics in Medicine and Biology

• Publication date

  2020-07-20

• Fields of study

  Medicine, Physics, Computer Science, Engineering

• Identifiers
  DOI 10.1088/1361-6560/aba798PMID 32688357
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Performance comparison of modified ComBat for harmonization of radiomic features for multicenter studies

  2020influential reference
• Effects of MRI image normalization techniques in prostate cancer radiomics.

  2020cited by this paper
• Outcome prediction of head and neck squamous cell carcinoma by MRI radiomic signatures

  2020cited by this paper
• Performance comparison of modified ComBat for harmonization of radiomic features for multicenter studies

  2020cited by this paper
• Experimental Multicenter and Multivendor Evaluation of the Performance of PET Radiomic Features Using 3-Dimensionally Printed Phantom Inserts

  2020cited by this paper
• Gray-level discretization impacts reproducible MRI radiomics texture features

  2019cited by this paper
• Radiomics robustness assessment and classification evaluation: A two-stage method demonstrated on multivendor FFDM.

  2019cited by this paper
• Creating Robust Predictive Radiomic Models for Data From Independent Institutions Using Normalization

  2019influential reference
• Validation of A Method to Compensate Multicenter Effects Affecting CT Radiomics.

  2019cited by this paper
• Pretreatment 18F-FDG PET/CT Radiomics Predict Local Recurrence in Patients Treated with Stereotactic Body Radiotherapy for Early-Stage Non–Small Cell Lung Cancer: A Multicentric Study

  2019cited by this paper
• Validation of a method to compensate multicenter effects affecting CT radiomic features

  2019cited by this paper
• Pre ‐ treatment 18 F -F DG PET/CT radiomics predict local recurrence in patients treated with stereotactic radiotherapy for early ‐ stage non ‐ small cell lung cancer: a multicentric study

  2019cited by this paper
• ComBat harmonization for radiomic features in independent phantom and lung cancer patient computed tomography datasets

  2019cited by this paper
• MRI derived radiomics: Methodology and clinical applications in the field of pelvic oncology.

  2019cited by this paper
• Experimental Multicenter And Multivendor Evaluation Of Pet Radiomic Features Performance Using 3d Printed Phantom Inserts

  2019cited by this paper
• Radiomic analysis for pretreatment prediction of response to neoadjuvant chemotherapy in locally advanced cervical cancer: A multicentre study

  2019cited by this paper
• Learning from scanners: Bias reduction and feature correction in radiomics

  2019cited by this paper
• The use of a proposed updated EARL harmonization of 18F-FDG PET-CT in patients with lymphoma yields significant differences in Deauville score compared with current EARL recommendations

  2019cited by this paper
• Radiomics in nuclear medicine: robustness, reproducibility, standardization, and how to avoid data analysis traps and replication crisis

  2019cited by this paper
• Reproducibility and Generalizability in Radiomics Modeling: Possible Strategies in Radiologic and Statistical Perspectives

  2019cited by this paper
• Deep Learning-based Image Conversion of CT Reconstruction Kernels Improves Radiomics Reproducibility for Pulmonary Nodules or Masses.

  2019cited by this paper
• Neural network training for cross-protocol radiomic feature standardization in computed tomography

  2019cited by this paper
• Stability of radiomic features of apparent diffusion coefficient (ADC) maps for locally advanced rectal cancer in response to image pre-processing.

  2019cited by this paper
• Repeatability and reproducibility of MRI-based radiomic features in cervical cancer.

  2019cited by this paper
• Predicting malignant nodules by fusing deep features with classical radiomics features

  2018cited by this paper
• Repeatability of Multiparametric Prostate MRI Radiomics Features

  2018cited by this paper
• Voxel size and gray level normalization of CT radiomic features in lung cancer

  2018cited by this paper
• A Postreconstruction Harmonization Method for Multicenter Radiomic Studies in PET

  2018cited by this paper
• Feasibility of state of the art PET/CT systems performance harmonisation

  2018cited by this paper
• Simulation and Synthesis in Medical Imaging

  2018cited by this paper
• Prediction of outcome using pretreatment 18F-FDG PET/CT and MRI radiomics in locally advanced cervical cancer treated with chemoradiotherapy

  2018cited by this paper
• Why validation of prognostic models matters?

  2018cited by this paper
• External validation of a combined PET and MRI radiomics model for prediction of recurrence in cervical cancer patients treated with chemoradiotherapy

  2018influential reference
• Deep Learning based Radiomics (DLR) and its usage in noninvasive IDH1 prediction for low grade glioma

  2017cited by this paper
• Prediction of cervical cancer recurrence using textural features extracted from 18F-FDG PET images acquired with different scanners

  2017cited by this paper
• EANM/EARL harmonization strategies in PET quantification: from daily practice to multicentre oncological studies

  2017cited by this paper
• Quantitative radiomics studies for tissue characterization: a review of technology and methodological procedures

  2017cited by this paper
• Dynamics and function of CXCR4 in formation of the granule cell layer during hippocampal development

  2017cited by this paper
• Harmonization of multi-site diffusion tensor imaging data

  2017cited by this paper
• Robustness of intratumour 18 F-FDG PET uptake heterogeneity quantification for therapy response prediction in ooesophageal carcinoma

  2017cited by this paper
• Post-radiochemotherapy PET radiomics in head and neck cancer - The influence of radiomics implementation on the reproducibility of local control tumor models.

  2017cited by this paper
• Why Batch Effects Matter in Omics Data, and How to Avoid Them.

  2017cited by this paper
• OC-0160: Radiomics Features Harmonization for CT and CBCT in Rectal Cancer

  2017cited by this paper
• Intrinsic dependencies of CT radiomic features on voxel size and number of gray levels

  2017cited by this paper
• Deep Feature Transfer Learning in Combination with Traditional Features Predicts Survival Among Patients with Lung Adenocarcinoma

  2016cited by this paper
• Impact of image preprocessing on the volume dependence and prognostic potential of radiomics features in non-small cell lung cancer

  2016cited by this paper
• Distributed learning: Developing a predictive model based on data from multiple hospitals without data leaving the hospital - A real life proof of concept.

  2016cited by this paper
• Applications and limitations of radiomics

  2016cited by this paper
• Repeatability of Radiomic Features in Non-Small-Cell Lung Cancer [18F]FDG-PET/CT Studies: Impact of Reconstruction and Delineation

  2016cited by this paper
• Characterization of PET/CT images using texture analysis: the past, the present… any future?

  2016cited by this paper
• Imaging biomarker roadmap for cancer studies

  2016cited by this paper
• Computational resources for radiomics

  2016cited by this paper
• 18F-FDG PET/CT heterogeneity quantification through textural features in the era of harmonisation programs: a focus on lung cancer

  2016cited by this paper
• 18F-FDG PET Uptake Characterization Through Texture Analysis: Investigating the Complementary Nature of Heterogeneity and Functional Tumor Volume in a Multi–Cancer Site Patient Cohort

  2015cited by this paper
• PNAS Plus Significance Statements

  2015cited by this paper
• Haralick texture analysis of prostate MRI: utility for differentiating non-cancerous prostate from prostate cancer and differentiating prostate cancers with different Gleason scores

  2015cited by this paper
• The effect of SUV discretization in quantitative FDG-PET Radiomics: the need for standardized methodology in tumor texture analysis

  2015cited by this paper
• The method and efficacy of support vector machine classifiers based on texture features and multi-resolution histogram from (18)F-FDG PET-CT images for the evaluation of mediastinal lymph nodes in patients with lung cancer.

  2015cited by this paper
• Measuring Computed Tomography Scanner Variability of Radiomics Features

  2015cited by this paper
• Impact of Image Reconstruction Settings on Texture Features in 18F-FDG PET

  2015cited by this paper
• Radiomics: Images Are More than Pictures, They Are Data

  2015cited by this paper
• 18F-FDG PET-Derived Textural Indices Reflect Tissue-Specific Uptake Pattern in Non-Small Cell Lung Cancer

  2015cited by this paper
• The Global Epidemiology of Impetigo: A Systematic Review of the Population Prevalence of Impetigo and Pyoderma

  2015cited by this paper
• Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

  2014cited by this paper
• Reproducibility and Prognosis of Quantitative Features Extracted from CT Images.

  2014cited by this paper
• FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0

  2014cited by this paper
• Robustness of intratumour 18F-FDG PET uptake heterogeneity quantification for therapy response prediction in oesophageal carcinoma

  2013cited by this paper
• Batch effect removal methods for microarray gene expression data integration: a survey

  2013cited by this paper
• Quantitative analysis of multiparametric prostate MR images: differentiation between prostate cancer and normal tissue and correlation with Gleason score--a computer-aided diagnosis development study.

  2013cited by this paper
• Are Pretreatment 18F-FDG PET Tumor Textural Features in Non–Small Cell Lung Cancer Associated with Response and Survival After Chemoradiotherapy?

  2013cited by this paper
• Radiomics: the process and the challenges.

  2012cited by this paper
• Reproducibility of Tumor Uptake Heterogeneity Characterization Through Textural Feature Analysis in 18F-FDG PET

  2012cited by this paper
• Using control genes to correct for unwanted variation in microarray data.

  2012cited by this paper
• Radiomics: extracting more information from medical images using advanced feature analysis.

  2012influential reference
• Intratumor Heterogeneity Characterized by Textural Features on Baseline 18F-FDG PET Images Predicts Response to Concomitant Radiochemotherapy in Esophageal Cancer

  2011cited by this paper
• Removing Batch Effects in Analysis of Expression Microarray Data: An Evaluation of Six Batch Adjustment Methods

  2011cited by this paper
• Thawing Frozen Robust Multi-array Analysis (fRMA)

  2011cited by this paper
• Tackling the widespread and critical impact of batch effects in high-throughput data

  2010cited by this paper
• Frozen robust multiarray analysis (fRMA).

  2010cited by this paper
• A comparison of batch effect removal methods for enhancement of prediction performance using MAQC-II microarray gene expression data

  2010cited by this paper
• Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters

  2010cited by this paper
• Coregistered FDG PET/CT-Based Textural Characterization of Head and Neck Cancer for Radiation Treatment Planning

  2009cited by this paper
• Batch Effects and Noise in Microarray Experiments: Sources and Solutions

  2009cited by this paper
• Class dependent feature scaling method using naive Bayes classifier for text datamining

  2009cited by this paper
• The removal of multiplicative, systematic bias allows integration of breast cancer gene expression datasets – improving meta-analysis and prediction of prognosis

  2008cited by this paper
• Merging two gene-expression studies via cross-platform normalization

  2008cited by this paper
• Capturing Heterogeneity in Gene Expression Studies by “ Surrogate Variable Analysis ”

  2007cited by this paper
• An attempt for combining microarray data sets by adjusting gene expressions.

  2007cited by this paper
• Adjusting batch effects in microarray expression data using empirical Bayes methods.

  2007cited by this paper
• Capturing Heterogeneity in Gene Expression Studies by Surrogate Variable Analysis

  2007cited by this paper
• Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

  2005cited by this paper
• Adjustment of systematic microarray data biases

  2004cited by this paper
• Influence of MRI acquisition protocols and image intensity normalization methods on texture classification.

  2004cited by this paper
• Model-based analysis of oligonucleotide arrays: expression index computation and outlier detection.

  2001cited by this paper
• Feature normalization and likelihood-based similarity measures for image retrieval

  2001cited by this paper

• Editorial to "Enhancing Study Design and Analysis of MR Imaging Markers Through Measurement Error Modeling".

  2026cites this paper
• 18F-FDG PET radiomic analysis to predict outcomes in metastatic melanoma treated with immune checkpoint inhibitors

  2026cites this paper
• Prostate Cancer Radiomic Features: Limited Cross‐Scanner Reproducibility Despite High Reader Reliability

  2026cites this paper
• SUV harmonization in the era of advanced PET: a necessary recalibration

  2026cites this paper
• Influence of CT harmonization in longitudinal radiomics for NSCLC immunotherapy response prediction.

  2026cites this paper
• Variability Regularized Feature Selection (VaRFS) for optimal identification of robust and discriminable features from medical imaging

  2026cites this paper
• Multimodal CT radiomics predicts PD-1 inhibitor efficacy in advanced gastric cancer: a two-center validation study

  2025cites this paper
• From Radical Resection to Precision Surgery: Integrating Diagnostic Biomarkers, Radiomics-Based Predictive Models, and Perioperative Systemic Therapy in Head and Neck Oncology

  2025cites this paper
• Explainable Artificial Intelligence for Multi-Modal Cancer Analysis: From Genomics to Immunology.

  2025cites this paper
• Evaluating Transferability of ComBat Harmonization of Diffusion Tensor Magnetic Resonance Imaging Data

  2025cites this paper
• Leveraging artificial intelligence to validate traditional biomarkers and drug targets in liver cancer recovery: a mini review

  2025cites this paper
• Exploring the complexities of radiomics: an in-depth analysis of a machine learning pipeline for predicting rectal cancer therapy response using MRI

  2025cites this paper
• Radiomics in preclinical imaging research: methods, challenges and opportunities

  2025cites this paper
• Overview of Challenges in Brain-based Predictive Modeling: Towards meaningful predictive insights.

  2025cites this paper
• PET-based radiomic analysis in multicentre lung cancer study and impact of feature domain harmonization

  2025cites this paper
• Ensuring Reproducibility and Deploying Models with the Image2Radiomics Framework: An Evaluation of Image Processing on PanNET Model Performance

  2025cites this paper
• Accurate Paediatric Brain Tumour Classification Through Improved Quantitative Analysis of 1H MR Imaging and Spectroscopy

  2025cites this paper
• Integrating Radiogenomics and Machine Learning in Musculoskeletal Oncology Care

  2025cites this paper
• The influence of image selection and segmentation on the extraction of lung cancer imaging radiomics features using 3D-Slicer software

  2025cites this paper
• Impact of harmonization and oversampling methods on radiomics analysis of multi-center imbalanced datasets: application to PET-based prediction of lung cancer subtypes

  2025cites this paper
• Impact of harmonization on predicting complications in head and neck cancer after radiotherapy using MRI radiomics and machine learning techniques

  2025cites this paper
• Temporal Validation of an FDG-PET-Radiomic Model for Distant-Relapse-Free-Survival After Radio-Chemotherapy for Pancreatic Adenocarcinoma

  2025cites this paper
• Multiparametric MRI for differentiating idiopathic granulomatous mastitis from invasive breast cancer:Improving radiologists' diagnostic accuracy.

  2025cites this paper
• Enhancing predictability of IDH mutation status in glioma patients at initial diagnosis: a comparative analysis of radiomics from MRI, [18F]FET PET, and TSPO PET

  2024cites this paper
• A neural network to create super‐resolution MR from multiple 2D brain scans of pediatric patients

  2024cites this paper
• The Challenge of External Generalisability: Insights from the Bicentric Validation of a [68Ga]Ga-PSMA-11 PET Based Radiomics Signature for Primary Prostate Cancer Characterisation Using Histopathology as Reference

  2024cites this paper
• Radiomics Harmonization in Ultrasound Images for Cervical Cancer Lymph Node Metastasis Prediction Using Cycle-GAN

  2024cites this paper
• Impact of intensity standardisation and ComBat batch size on clinical-radiomic prognostic models performance in a multi-centre study of patients with glioblastoma

  2024cites this paper
• Impact of Harmonization on MRI Radiomics Feature Variability Across Preprocessing Methods for Parkinson’s Disease Motor Subtype Classification

  2024cites this paper
• Long-axial field-of-view PET/CT improves radiomics feature reliability

  2024cites this paper
• Myocardial perfusion SPECT radiomic features reproducibility assessment: Impact of image reconstruction and harmonization

  2024cites this paper
• Impact of Leakage on Data Harmonization in Machine Learning Pipelines in Class Imbalance Across Sites

  2024cites this paper
• Mitigating Interobserver Variability in Radiomics with ComBat: A Feasibility Study

  2024cites this paper
• Contrast Enhanced CT Radiogenomics in a Retrospective NSCLC Cohort: Models, Attempted Validation of a Published Model and the Relevance of the Clinical Context.

  2024cites this paper
• PET radiomics in lung cancer: advances and translational challenges

  2024cites this paper
• Deep feature batch correction using ComBat for machine learning applications in computational pathology

  2024cites this paper
• Deep Learning for MRI Segmentation and Molecular Subtyping in Glioblastoma: Critical Aspects from an Emerging Field

  2024cites this paper
• Habitat Imaging With Tumoral and Peritumoral Radiomics for Prediction of Lung Adenocarcinoma Invasiveness on Preoperative Chest CT: A Multicenter Study.

  2024cites this paper
• A novel assessment of whole-mount Gleason grading in prostate cancer to identify candidates for radical prostatectomy: a machine learning-based multiomics study

  2024cites this paper
• Multimodal Imaging Approach for Tumor Treatment Response Evaluation in the Era of Immunotherapy.

  2024cites this paper
• Review on radiomic analysis in 18F-fluorodeoxyglucose positron emission tomography for prediction of melanoma outcomes

  2024cites this paper
• Multiparametric MRI-based radiomic model for predicting lymph node metastasis after neoadjuvant chemoradiotherapy in locally advanced rectal cancer

  2024cites this paper
• Multivariate testing and effect size measures for batch effect evaluation in radiomic features

  2024cites this paper
• Magnetic resonance imaging radiomic features stability in brain metastases: Impact of image preprocessing, image-, and feature-level harmonization

  2024influential citation
• Impact of harmonization on the reproducibility of MRI radiomic features when using different scanners, acquisition parameters, and image pre-processing techniques: a phantom study

  2024influential citation
• Radiomics in stereotactic body radiotherapy for non-small cell lung cancer: a systematic review and radiomic quality score study

  2024cites this paper
• Comparative analysis of batch correction methods for FDG PET/CT using metabolic radiogenomic data of lung cancer patients

  2023cites this paper
• A review of harmonization strategies for quantitative PET

  2023cites this paper
• Risk Assessment and Pancreatic Cancer: Diagnostic Management and Artificial Intelligence

  2023cites this paper
• Dual adversarial deconfounding autoencoder for joint batch-effects removal from multi-center and multi-scanner radiomics data

  2023cites this paper
• Feasibility of radiomic feature harmonization for pooling of [18F]FET or [18F]GE-180 PET images of gliomas.

  2023cites this paper
• The application of artificial intelligence in the detection of basal cell carcinoma: A systematic review

  2023cites this paper
• Explainable domain transfer of distant supervised cancer subtyping model via imaging-based rules extraction

  2023cites this paper
• Colorectal liver metastases patients prognostic assessment: prospects and limits of radiomics and radiogenomics

  2023cites this paper
• Long-axial field-of-view PET/CT: perspectives and review of a revolutionary development in nuclear medicine based on clinical experience in over 7000 patients

  2023cites this paper
• Prognostic value of pre-therapeutic FDG-PET radiomic analysis in gastro-esophageal junction cancer

  2023cites this paper
• Image harmonization: A review of statistical and deep learning methods for removing batch effects and evaluation metrics for effective harmonization

  2023cites this paper
• Differentiation of benign versus malignant indistinguishable vertebral compression fractures by different machine learning with MRI-based radiomic features

  2023cites this paper
• Radiomic analysis for early differentiation of lung cancer recurrence from fibrosis in patients treated with lung stereotactic ablative radiotherapy

  2023cites this paper
• Normalization Strategies in Multi-Center Radiomics Abdominal MRI: Systematic Review and Meta-Analyses

  2023cites this paper
• Could normalization improve robustness of abdominal MRI radiomic features?

  2023cites this paper
• Prediction of synchronous distant metastasis of primary pancreatic ductal adenocarcinoma using the radiomics features derived from 18F-FDG PET and MRI.

  2023cites this paper
• Data and model aggregation for radiomics applications: Emerging trend and open challenges

  2023cites this paper
• Generalization optimizing machine learning to improve CT scan radiomics and assess immune checkpoint inhibitors’ response in non-small cell lung cancer: a multicenter cohort study

  2023cites this paper
• Dual-Centre Harmonised Multimodal Positron Emission Tomography/Computed Tomography Image Radiomic Features and Machine Learning Algorithms for Non-small Cell Lung Cancer Histopathological Subtype Phenotype Decoding.

  2023cites this paper
• The Effect of Image Resampling on the Performance of Radiomics‐Based Artificial Intelligence in Multicenter Prostate MRI

  2023cites this paper
• Development and validation of a contrast-enhanced CT-based radiomics nomogram for differentiating mass-like thymic hyperplasia and low-risk thymoma

  2023cites this paper
• Prognostic Assessment of Gastropancreatic Neuroendocrine Neoplasm: Prospects and Limits of Radiomics

  2023cites this paper
• Radiomics and machine learning analysis by computed tomography and magnetic resonance imaging in colorectal liver metastases prognostic assessment

  2023cites this paper
• A systematic review of radiomics for predicting treatment response and survival in locally advanced cervical cancer: positive results or optimistic illusions?

  2023cites this paper
• Computed Tomography-derived intratumoral and peritumoral radiomics in predicting EGFR mutation in lung adenocarcinoma

  2023cites this paper
• Optimal batch determination for improved harmonization and prognostication of multi-center PET/CT radiomics feature in head and neck cancer

  2023cites this paper
• Enhancing Interoperability and Harmonisation of Nuclear Medicine Image Data and Associated Clinical Data

  2023cites this paper
• Investigating the role of imaging factors in the variability of CT‐based texture analysis metrics

  2023cites this paper
• Standardized brain tumor imaging protocols for clinical trials: current recommendations and tips for integration

  2023cites this paper
• Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions

  2022cites this paper
• ["Adaptation of the tumour and its ecosystem to radiotherapies: Mechanisms, imaging and therapeutic approaches" XIVth edition of the workshop organised by the "Vectorisation, Imagerie, Radiothérapies" network of the Cancéropôle Grand-Ouest, 22-25 September 2021, Le Bono, France].

  2022cites this paper
• Spatially coherent modeling of 3D FDG-PET data for assessment of intratumoral heterogeneity and uptake gradients

  2022cites this paper
• Feasibility of using CT radiomic signatures for predicting CD8-T cell infiltration and PD-L1 expression in renal cell carcinoma

  2022cites this paper
• Improved generalized ComBat methods for harmonization of radiomic features

  2022cites this paper
• Harmonization Strategies in Multicenter MRI-Based Radiomics

  2022cites this paper
• Deep learning–based harmonization of CT reconstruction kernels towards improved clinical task performance

  2022cites this paper
• Radiomics in clinical trials: perspectives on standardization

  2022cites this paper
• External validation of an MR-based radiomic model predictive of locoregional control in oropharyngeal cancer

  2022cites this paper
• A Framework of Analysis to Facilitate the Harmonization of Multicenter Radiomic Features in Prostate Cancer

  2022cites this paper
• Textural Analysis as a Predictive Biomarker in Rectal Cancer

  2022cites this paper
• AutoComBat: a generic method for harmonizing MRI-based radiomic features

  2022cites this paper
• Impact of image quality on radiomics applications

  2022cites this paper
• Quality of Multicenter Studies Using MRI Radiomics for Diagnosing Clinically Significant Prostate Cancer: A Systematic Review

  2022cites this paper
• Impact of feature harmonization on radiogenomics analysis: Prediction of EGFR and KRAS mutations from non-small cell lung cancer PET/CT images

  2022cites this paper
• Joint EANM/SNMMI guideline on radiomics in nuclear medicine

  2022cites this paper
• Harmonisation of scanner-dependent contrast variations in magnetic resonance imaging for radiation oncology, using style-blind auto-encoders

  2022cites this paper
• Radiomics-guided radiation therapy: opportunities and challenges

  2022cites this paper
• Intensity standardization of MRI prior to radiomic feature extraction for artificial intelligence research in glioma—a systematic review

  2022cites this paper
• Noise-Based Image Harmonization Significantly Increases Repeatability and Reproducibility of Radiomics Features in PET Images: A Phantom Study

  2022cites this paper
• External validation and comparison of MR-based radiomics models for predicting pathological complete response in locally advanced rectal cancer: a two-centre, multi-vendor study

  2022cites this paper
• Beads phantom for evaluating heterogeneity of SUV on 18F-FDG PET images

  2022cites this paper
• Iterative ComBat methods for harmonization of radiomic features

  2022cites this paper
• Context-Aware Saliency Guided Radiomics: Application to Prediction of Outcome and HPV-Status from Multi-Center PET/CT Images of Head and Neck Cancer

  2022cites this paper
• Generalized ComBat harmonization methods for radiomic features with multi-modal distributions and multiple batch effects

  2022cites this paper