ReviewEuropean journal of nuclear medicine and molecular imaging2019
AI-based applications in hybrid imaging: how to build smart and truly multi-parametric decision models for radiomics.
Review in European journal of nuclear medicine and molecular imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Trial
- Review of Artificial Intelligence Techniques for Breast Cancer Detection with Different Modalities: Mammography, Ultrasound, and Thermography Images.Bioengineering (Basel, Switzerland) · 2025Review
- CT radiomics to assess severity of explosion-induced primary blast lung injury in goats.Scientific reports · 2025Article
- Robust radiomics: a review of guidelines for radiomics in medical imaging.Frontiers in radiology · 2025Review
- A nomogram based on radiomics and clinical information to predict prognosis in percutaneous balloon compression for the treatment of trigeminal neuralgia.Neurosurgical review · 2024Article
- [A clinical-radiomics nomogram for differentiating focal organizing pneumonia and lung adenocarcinoma].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2024Article
- Machine learning to predict radiomics models of classical trigeminal neuralgia response to percutaneous balloon compression treatment.Frontiers in neurology · 2024Article
- Radiomics Analyses to Predict Histopathology in Patients with Metastatic Testicular Germ Cell Tumors before Post-Chemotherapy Retroperitoneal Lymph Node Dissection.Journal of imaging · 2023Article
- Predicting pathological highly invasive lung cancer from preoperative [European journal of nuclear medicine and molecular imaging · 2023Article
- Deep pathomics: A new image-based tool for predicting response to treatment in stage III non-small cell lung cancer.PloS one · 2023Article
- Utility of quantitative MRI metrics in brain ageing research.Frontiers in aging neuroscience · 2023Article
- Artificial Intelligence (AI) in Breast Imaging: A Scientometric Umbrella Review.Diagnostics (Basel, Switzerland) · 2022Review
- Ultrasound radiomics in personalized breast management: Current status and future prospects.Frontiers in oncology · 2022Review
- Pre-Processing Method for Contouring the Uptake Levels of [18F] FDG for Enhanced Specificity of PET Imaging of Solitary Hypermetabolic Pulmonary Nodules.Journal of clinical medicine · 2021Article
- Advanced Imaging Analysis in Prostate MRI: Building a Radiomic Signature to Predict Tumor Aggressiveness.Diagnostics (Basel, Switzerland) · 2021Article
- Breast Tumor Characterization Using [Cancers · 2021Article
- Radiomics for Identification and Prediction in Metastatic Prostate Cancer: A Review of Studies.Frontiers in oncology · 2021Review
- Classifying Ruptured Middle Cerebral Artery Aneurysms With a Machine Learning Based, Radiomics-Morphological Model: A Multicentral Study.Frontiers in neuroscience · 2021Article
- Radiomics and deep learning in lung cancer.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2020Review
- Electron Density and Biologically Effective Dose (BED) Radiomics-Based Machine Learning Models to Predict Late Radiation-Induced Subcutaneous Fibrosis.Frontiers in oncology · 2020Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe quantitative imaging features (radiomics) that can be obtained from the different modalities of current-generation hybrid imaging can give complementary information with regard to the tumour environment, as they measure different morphologic and functional imaging properties. These multi-parametric image descriptors can be combined with artificial intelligence applications into predictive models. It is now the time for hybrid PET/CT and PET/MRI to take the advantage offered by radiomics to assess the added clinical benefit of using multi-parametric models for the personalized diagnosis and prognosis of different disease phenotypes.
objectiveThe aim of the paper is to provide an overview of current challenges and available solutions to translate radiomics into hybrid PET-CT and PET-MRI imaging for a smart and truly multi-parametric decision model.
Indexed as
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31292700What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.