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False Discovery Rates in PET and CT Studies with Texture Features: A Systematic Review
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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inferred← citeshttps://doi.org/10.1007/s12149-019-01414-0openalex-snapshot
Usefulness of gradient tree boosting for predicting histological subtype and EGFR mutation status of non-small cell lung cancer on 18F FDG-PET/CT
inferred← citeshttps://doi.org/10.1007/s12350-022-02927-4openalex-snapshot
A methodological framework for AI-assisted diagnosis of active aortitis using radiomic analysis of FDG PET–CT images: Initial analysis
inferred← citeshttps://doi.org/10.1007/s13139-017-0500-yopenalex-snapshot
Radiomics in Oncological PET/CT: Clinical Applications
inferred← citeshttps://doi.org/10.1007/s40336-018-0299-2openalex-snapshot
Heterogeneity analysis of 18F-FDG PET imaging in oncology: clinical indications and perspectives
inferred← citeshttps://doi.org/10.1007/s40336-018-0302-yopenalex-snapshot
Radiomics: is it time to compose the puzzle?
inferred← citeshttps://doi.org/10.1007/s40846-021-00671-7openalex-snapshot
Measuring Heterogeneity in 18F-Fluorodeoxyglucose Positron Emission Tomography Images for Classifying Metastatic and Benign Bone Lesions in Patients with Cervical Cancer
inferred← citeshttps://doi.org/10.1016/b978-0-12-819872-8.00018-5openalex-snapshot
Role of artificial intelligence and radiomics in diagnosing renal tumors: a survey
inferred← citeshttps://doi.org/10.1016/b978-0-12-820951-6.00011-9openalex-snapshot
Imaging epigenetics and the radiogenomics
inferred← citeshttps://doi.org/10.1016/b978-0-12-822000-9.00009-4openalex-snapshot
Radiomics: “unlocking the potential of medical images for precision radiation oncology”
inferred← citeshttps://doi.org/10.1016/j.acra.2021.04.014openalex-snapshot
CT Radiomics Features in Differentiation of Focal-Type Autoimmune Pancreatitis from Pancreatic Ductal Adenocarcinoma: A Propensity Score Analysis
inferred← citeshttps://doi.org/10.1016/j.acra.2022.10.008openalex-snapshot
T2-Weighted Image Radiomics Nomogram to Predict Pancreatic Serous and Mucinous Cystic Neoplasms
inferred← citeshttps://doi.org/10.1016/j.acra.2022.10.030openalex-snapshot
Virtual Image-based Biopsy of Lung Metastases: The Promise of Radiomics
inferred← citeshttps://doi.org/10.1016/j.acra.2024.02.028openalex-snapshot
Use of Response Permutation to Measure an Imaging Dataset’s Susceptibility to Overfitting by Selected Standard Analysis Pipelines
inferred← citeshttps://doi.org/10.1016/j.bpg.2018.11.009openalex-snapshot
Novel imaging techniques in staging oesophageal cancer
inferred← citeshttps://doi.org/10.1016/j.brachy.2023.06.004openalex-snapshot
A general framework to develop a radiomic fingerprint for progression-free survival in cervical cancer
inferred← citeshttps://doi.org/10.1016/j.clinimag.2024.110275openalex-snapshot
“Application of CT radiomics in brain metastasis of lung cancer: A systematic review and meta-analysis”
inferred← citeshttps://doi.org/10.1016/j.clon.2021.10.006openalex-snapshot
Radiomics for Predicting Lung Cancer Outcomes Following Radiotherapy: A Systematic Review
inferred← citeshttps://doi.org/10.1016/j.clon.2024.03.003openalex-snapshot
Radiomics for clinical decision support in radiation oncology
inferred← citeshttps://doi.org/10.1016/j.cmpb.2023.107714openalex-snapshot
Fusion-based tensor radiomics using reproducible features: Application to survival prediction in head and neck cancer
inferred← citeshttps://doi.org/10.1016/j.cmpb.2025.108771openalex-snapshot
Combining radiomics and connectomics in MRI studies of the human brain: A systematic literature review
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2020.103962openalex-snapshot
A lung graph model for the radiological assessment of chronic thromboembolic pulmonary hypertension in CT
inferred← citeshttps://doi.org/10.1016/j.cpet.2019.08.009openalex-snapshot
18F-Fluorodeoxyglucose PET in Locally Advanced Non–small Cell Lung Cancer
inferred← citeshttps://doi.org/10.1016/j.crad.2016.03.013openalex-snapshot
Multi-technique hybrid imaging in PET/CT and PET/MR: what does the future hold?
inferred← citeshttps://doi.org/10.1016/j.crad.2016.09.013openalex-snapshot
Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging
inferred← citeshttps://doi.org/10.1016/j.crad.2019.04.017openalex-snapshot
Artificial intelligence and radiomics in pulmonary nodule management: current status and future applications
inferred← citeshttps://doi.org/10.1016/j.crad.2021.01.001openalex-snapshot
Opportunities in cancer imaging: a review of oesophageal, gastric and colorectal malignancies
inferred← citeshttps://doi.org/10.1016/j.crad.2024.04.022openalex-snapshot
Predicting histopathological features of aggressiveness in lung cancer using CT radiomics: a systematic review
inferred← citeshttps://doi.org/10.1016/j.crad.2025.106952openalex-snapshot
Elucidating the biological function of computed tomography (CT)-based radiomics biomarkers in serous ovarian cancer
inferred← citeshttps://doi.org/10.1016/j.critrevonc.2019.03.015openalex-snapshot
Radiomics: Principles and radiotherapy applications
inferred← citeshttps://doi.org/10.1016/j.ctro.2021.03.006openalex-snapshot
Radiomic biomarkers of tumor immune biology and immunotherapy response
inferred← citeshttps://doi.org/10.1016/j.ebiom.2019.03.050openalex-snapshot
Pretreatment MRI radiomics analysis allows for reliable prediction of local recurrence in non-metastatic T4 nasopharyngeal carcinoma
inferred← citeshttps://doi.org/10.1016/j.ejmp.2019.11.026openalex-snapshot
Homological radiomics analysis for prognostic prediction in lung cancer patients
inferred← citeshttps://doi.org/10.1016/j.ejmp.2020.02.010openalex-snapshot
Machine learning helps identifying volume-confounding effects in radiomics
inferred← citeshttps://doi.org/10.1016/j.ejrad.2019.02.006openalex-snapshot
Prognostic modeling for patients with colorectal liver metastases incorporating FDG PET radiomic features
inferred← citeshttps://doi.org/10.1016/j.ejrad.2019.07.018openalex-snapshot
Radiomic analysis for preoperative prediction of cervical lymph node metastasis in patients with papillary thyroid carcinoma
inferred← citeshttps://doi.org/10.1016/j.ejrad.2020.108991openalex-snapshot
A review of original articles published in the emerging field of radiomics
inferred← citeshttps://doi.org/10.1016/j.ejrad.2020.109448openalex-snapshot
Artificial intelligence applications for oncological positron emission tomography imaging
inferred← citeshttps://doi.org/10.1016/j.ejrad.2026.112890openalex-snapshot
Decomposing performance inflation in radiomics: factorial quantification of analytical leakage
inferred← citeshttps://doi.org/10.1016/j.ijrobp.2017.12.268openalex-snapshot
Challenges and Promises of PET Radiomics
inferred← citeshttps://doi.org/10.1016/j.ijrobp.2018.05.053openalex-snapshot
Repeatability and Reproducibility of Radiomic Features: A Systematic Review
inferred← citeshttps://doi.org/10.1016/j.iotech.2021.100028openalex-snapshot
Radiomics in immuno-oncology
inferred← citeshttps://doi.org/10.1016/j.jacr.2017.12.006openalex-snapshot
Translational Radiomics: Defining the Strategy Pipeline and Considerations for Application—Part 2: From Clinical Implementation to Enterprise
inferred← citeshttps://doi.org/10.1016/j.jbo.2019.100263openalex-snapshot
Radiomics signature extracted from diffusion-weighted magnetic resonance imaging predicts outcomes in osteosarcoma
inferred← citeshttps://doi.org/10.1016/j.jvir.2019.03.001openalex-snapshot
Risk Prediction for Early Biliary Infection after Percutaneous Transhepatic Biliary Stent Placement in Malignant Biliary Obstruction
inferred← citeshttps://doi.org/10.1016/j.mednuc.2019.09.001openalex-snapshot
Analyse texturale en TEP au FDG des cancers pulmonaires non à petites cellules de stade localement avancé : valeur pronostique de l’entropie
inferred← citeshttps://doi.org/10.1016/j.mednuc.2020.02.003openalex-snapshot
Value of 18FDG PET for prediction of therapeutic response in HER2+ breast cancer: Interim analysis
inferred← citeshttps://doi.org/10.1016/j.mri.2019.08.011openalex-snapshot
Comparison of machine learning classifiers for differentiation of grade 1 from higher gradings in meningioma: A multicenter radiomics study
inferred← citeshttps://doi.org/10.1016/j.mri.2021.10.024openalex-snapshot
Radiomic machine learning for pretreatment assessment of prognostic risk factors for endometrial cancer and its effects on radiologists' decisions of deep myometrial invasion
inferred← citeshttps://doi.org/10.1016/j.nicl.2017.08.021openalex-snapshot
Improved prediction of outcome in Parkinson's disease using radiomics analysis of longitudinal DAT SPECT images
inferred← citeshttps://doi.org/10.1016/j.oraloncology.2019.09.022openalex-snapshot
A multidimensional nomogram combining overall stage, dose volume histogram parameters and radiomics to predict progression-free survival in patients with locoregionally advanced nasopharyngeal carcinoma
inferred← citeshttps://doi.org/10.1016/j.phro.2021.10.007openalex-snapshot
A systematic review and quality of reporting checklist for repeatability and reproducibility of radiomic features
inferred← citeshttps://doi.org/10.1016/j.phrs.2021.105643openalex-snapshot
Combining liquid biopsy and radiomics for personalized treatment of lung cancer patients. State of the art and new perspectives
inferred← citeshttps://doi.org/10.1016/j.prro.2020.10.004openalex-snapshot
Validating the SumMean 18F-FDG PET Textural Feature as a Prognostic Marker in an Independent Cohort of Locally Advanced Non-Small Cell Lung Cancer Patients Undergoing Concurrent Chemoradiation Therapy
inferred← citeshttps://doi.org/10.1016/j.radonc.2018.03.004openalex-snapshot
Why validation of prognostic models matters?
inferred← citeshttps://doi.org/10.1016/j.radonc.2019.10.012openalex-snapshot
Heterogeneity in tumours: Validating the use of radiomic features on 18F-FDG PET/CT scans of lung cancer patients as a prognostic tool
inferred← citeshttps://doi.org/10.1016/j.rcl.2020.06.001openalex-snapshot
Radiomics and Artificial Intelligence for Renal Mass Characterization
inferred← citeshttps://doi.org/10.1016/j.ultrasmedbio.2020.12.012openalex-snapshot
Muscle Composition Analysis of Ultrasound Images: A Narrative Review of Texture Analysis
inferred← citeshttps://doi.org/10.1016/j.urology.2019.09.023openalex-snapshot
Contrast-enhanced CT Texture Parameters as Predictive Markers of High-risk Urodynamic Features in Adult Patients with Spina Bifida
inferred← citeshttps://doi.org/10.1016/s2589-7500(19)30062-7openalex-snapshot
Handcrafted versus deep learning radiomics for prediction of cancer therapy response
inferred← citeshttps://doi.org/10.1038/s41598-017-00426-yopenalex-snapshot
PET Radiomics in NSCLC: state of the art and a proposal for harmonization of methodology
inferred← citeshttps://doi.org/10.1038/s41598-017-00665-zopenalex-snapshot
Delta-radiomics features for the prediction of patient outcomes in non–small cell lung cancer
inferred← citeshttps://doi.org/10.1038/s41598-019-45766-zopenalex-snapshot
Repeatability of Multiparametric Prostate MRI Radiomics Features
inferred← citeshttps://doi.org/10.1038/s41598-019-46985-0openalex-snapshot
MRI-based radiomics signature is a quantitative prognostic biomarker for nasopharyngeal carcinoma
inferred← citeshttps://doi.org/10.1038/s41598-025-87778-yopenalex-snapshot
Using partially shared radiomics features to simultaneously identify isocitrate dehydrogenase mutation status and epilepsy in glioma patients from MRI images
inferred← citeshttps://doi.org/10.1038/s42003-021-02814-7openalex-snapshot
Radiomics-guided deep neural networks stratify lung adenocarcinoma prognosis from CT scans
inferred← citeshttps://doi.org/10.1038/s42256-021-00377-0openalex-snapshot
Radiological tumour classification across imaging modality and histology
inferred← citeshttps://doi.org/10.1038/s43856-022-00199-0openalex-snapshot
Artificial intelligence and machine learning in cancer imaging
inferred← citeshttps://doi.org/10.1038/srep16822openalex-snapshot
Fully automatic GBM segmentation in the TCGA-GBM dataset: Prognosis and correlation with VASARI features
inferred← citeshttps://doi.org/10.1053/j.semnuclmed.2017.01.001openalex-snapshot
Current Role of FDG-PET in Pediatric Hodgkin’s Lymphoma
inferred← citeshttps://doi.org/10.1053/j.semnuclmed.2020.05.002openalex-snapshot
A Role for FDG PET Radiomics in Personalized Medicine?
inferred← citeshttps://doi.org/10.1053/j.semnuclmed.2020.09.001openalex-snapshot
Artificial Intelligence for the Characterization of Pulmonary Nodules, Lung Tumors and Mediastinal Nodes on PET/CT
inferred← citeshttps://doi.org/10.1053/j.semnuclmed.2020.09.002openalex-snapshot
Radiomics in PET/CT: Current Status and Future AI-Based Evolutions
inferred← citeshttps://doi.org/10.1080/23311916.2024.2406377openalex-snapshot
An efficient pulmonary carcinoma nodule detection model
inferred← citeshttps://doi.org/10.1088/0031-9155/61/1/227openalex-snapshot
A novel metric for quantification of homogeneous and heterogeneous tumors in PET for enhanced clinical outcome prediction
inferred← citeshttps://doi.org/10.1088/0031-9155/61/13/r150openalex-snapshot
Applications and limitations of radiomics
inferred← citeshttps://doi.org/10.1088/1361-6560/aa6cf2openalex-snapshot
Factors influencing the robustness of P -value measurements in CT texture prognosis studies
inferred← citeshttps://doi.org/10.1088/1361-6560/ac2ea5openalex-snapshot
Generalized methodology for radiomic feature selection and modeling in predicting clinical outcomes
inferred← citeshttps://doi.org/10.1088/2057-1976/ac8e6fopenalex-snapshot
Radiomics software comparison using digital phantom and patient data: IBSI-compliance does not guarantee concordance of feature values
inferred← citeshttps://doi.org/10.1093/bioinformatics/btx438openalex-snapshot
The value of prior knowledge in machine learning of complex network systems
inferred← citeshttps://doi.org/10.1093/bjr/tqaf027openalex-snapshot
The current state of imaging biomarker development and evaluation
inferred← citeshttps://doi.org/10.1093/ije/dyaf098openalex-snapshot
Multiplicity corrections in life sciences: challenges and consequences
inferred← citeshttps://doi.org/10.1093/neuonc/noac100openalex-snapshot
Evaluation of magnetic resonance imaging-based radiomics characteristics for differentiation of benign and malignant peripheral nerve sheath tumors in neurofibromatosis type 1
inferred← citeshttps://doi.org/10.1093/ons/opz288openalex-snapshot
Magnetic Resonance-Based Radiomic Analysis of Radiofrequency Lesion Predicts Outcomes After Percutaneous Cordotomy: A Feasibility Study
inferred← citeshttps://doi.org/10.1097/mnm.0000000000001809openalex-snapshot
The added diagnostic value of 18F-FDG PET/CT radiomic analysis in multiple myeloma patients with negative visual analysis
inferred← citeshttps://doi.org/10.1097/mnm.0000000000001816openalex-snapshot
Preoperative prediction of microsatellite instability status: development and validation of a pan-cancer PET/CT-based radiomics model
inferred← citeshttps://doi.org/10.1097/rct.0000000000001742openalex-snapshot
Effectiveness of CT Histogram Analysis to Differentiate Lung Metastases From Second Primary Lung Cancer to Decrease Need for Lung Biopsy
inferred← citeshttps://doi.org/10.1097/rli.0000000000000666openalex-snapshot
Variability and Standardization of Quantitative Imaging
inferred← citeshttps://doi.org/10.1101/cshperspect.a039537openalex-snapshot
Application of Radiomics and Artificial Intelligence for Lung Cancer Precision Medicine
inferred← citeshttps://doi.org/10.1109/access.2023.3306515openalex-snapshot
Enhancing Prostate Cancer Classification by Leveraging Key Radiomics Features and Using the Fine-Tuned Linear SVM Algorithm
inferred← citeshttps://doi.org/10.1109/iccad60883.2024.10553720openalex-snapshot
Sensitivity of radiomics features to region volume: A CT phantom study
inferred← citeshttps://doi.org/10.1109/isbi.2019.8759318openalex-snapshot
Novel Radiomic Features Based on Graph Theory for PET Image Analysis
inferred← citeshttps://doi.org/10.1109/jbhi.2019.2956354openalex-snapshot
Multi-Level Multi-Modality Fusion Radiomics: Application to PET and CT Imaging for Prognostication of Head and Neck Cancer
inferred← citeshttps://doi.org/10.1109/trpms.2017.2777890openalex-snapshot
Prognostic Value of Head and Neck Tumor Proliferative Sphericity From 3’-Deoxy-3’-[18F] Fluorothymidine Positron Emission Tomography
inferred← citeshttps://doi.org/10.1109/trpms.2018.2844171openalex-snapshot
Use of Generative Disease Models for Analysis and Selection of Radiomic Features in PET
inferred← citeshttps://doi.org/10.1109/trpms.2019.2899538openalex-snapshot
Machine (Deep) Learning Methods for Image Processing and Radiomics
inferred← citeshttps://doi.org/10.1111/cpf.12908openalex-snapshot
The prognostic value of [18F]FDG PET/CT texture analysis prior to transplantation for unresectable colorectal liver metastases
inferred← citeshttps://doi.org/10.1117/12.2293864openalex-snapshot
The effects of variations in parameters and algorithm choices on calculated radiomics feature values: initial investigations and comparisons to feature variability across CT image acquisition conditions
inferred← citeshttps://doi.org/10.1148/radiol.2017162725openalex-snapshot
Added Value of Computer-aided CT Image Features for Early Lung Cancer Diagnosis with Small Pulmonary Nodules: A Matched Case-Control Study
inferred← citeshttps://doi.org/10.1148/radiol.211597openalex-snapshot
Radiomic Analysis: Study Design, Statistical Analysis, and Other Bias Mitigation Strategies
inferred← citeshttps://doi.org/10.1148/rg.2017170056openalex-snapshot
CT Texture Analysis: Definitions, Applications, Biologic Correlates, and Challenges
inferred← citeshttps://doi.org/10.1148/rg.2017170172openalex-snapshot
Invited Commentary on “CT Texture Analysis”
inferred← citeshttps://doi.org/10.1155/2018/3574310openalex-snapshot
Radiomic Profiling of Head and Neck Cancer: 18F-FDG PET Texture Analysis as Predictor of Patient Survival
inferred← citeshttps://doi.org/10.1155/2019/6584636openalex-snapshot
Differentiation of Pituitary Adenoma from Rathke Cleft Cyst: Combining MR Image Features with Texture Features
inferred← citeshttps://doi.org/10.1158/0008-5472.can-18-0125openalex-snapshot
LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characterization of Tumor Heterogeneity
inferred← citeshttps://doi.org/10.1158/1078-0432.ccr-16-2910openalex-snapshot
Radiomics Features of Multiparametric MRI as Novel Prognostic Factors in Advanced Nasopharyngeal Carcinoma
inferred← citeshttps://doi.org/10.1158/1078-0432.ccr-17-2754openalex-snapshot
HER3-Mediated Resistance to Hsp90 Inhibition Detected in Breast Cancer Xenografts by Affibody-Based PET Imaging
inferred← citeshttps://doi.org/10.1158/1078-0432.ccr-17-2804openalex-snapshot
Data Science in Radiology: A Path Forward
inferred← citeshttps://doi.org/10.1166/jmihi.2018.2509openalex-snapshot
Preliminary Study of Computed Tomography Texture Analysis in Pancreatic Cystadenoma
inferred← citeshttps://doi.org/10.1167/iovs.65.10.4openalex-snapshot
Recurrence in Eyelid Sebaceous Carcinoma: A Multicentric Study of 418 Patients
inferred← citeshttps://doi.org/10.1177/02841851211068149openalex-snapshot
Radiomics and stacking regression model for measuring bone mineral density using abdominal computed tomography
inferred← citeshttps://doi.org/10.1177/03000605241275338openalex-snapshot
Clinical value of a radiomics model based on machine learning for the prediction of prostate cancer
inferred← citeshttps://doi.org/10.1177/15330338221099396openalex-snapshot
The Effects of Automatic Segmentations on Preoperative Lymph Node Status Prediction Models With Ultrasound Radiomics for Patients With Early Stage Cervical Cancer
inferred← citeshttps://doi.org/10.1177/17562872221109020openalex-snapshot
Radiomics in prostate cancer: an up-to-date review
inferred← citeshttps://doi.org/10.1186/s12876-023-02743-1openalex-snapshot
Repeatability of radiomics studies in colorectal cancer: a systematic review
inferred← citeshttps://doi.org/10.1186/s12885-025-14466-5openalex-snapshot
Deep learning radiomics and mediastinal adipose tissue-based nomogram for preoperative prediction of postoperative brain metastasis risk in non-small cell lung cancer
inferred← citeshttps://doi.org/10.1186/s13244-020-00887-2openalex-snapshot
Radiomics in medical imaging—“how-to” guide and critical reflection
inferred← citeshttps://doi.org/10.1186/s13244-021-01153-9openalex-snapshot
A review on advances in 18F-FDG PET/CT radiomics standardisation and application in lung disease management
inferred← citeshttps://doi.org/10.1186/s13244-022-01245-0openalex-snapshot
Radiomic assessment of oesophageal adenocarcinoma: a critical review of 18F-FDG PET/CT, PET/MRI and CT
inferred← citeshttps://doi.org/10.1186/s13244-025-01940-8openalex-snapshot
Should all trainees “do research”?
inferred← citeshttps://doi.org/10.1186/s13244-025-01954-2openalex-snapshot
Reply to the Letter to the Editor: Should all trainees “do research”?
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