Results 31 to 40 of about 55,768 (244)
Insights into Imaging, 2022 Objective To develop and validate an 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT)-based radiomics nomogram for non-invasively prediction of bone marrow involvement (BMI) in pediatric neuroblastoma.
Lijuan Feng +8 more
doaj +1 more source
Frontiers in Neurology, 2021 Objectives: To investigate the association between radiomics features and epilepsy in patients with unruptured brain arteriovenous malformations (bAVMs) and to develop a prediction model based on radiomics features and clinical characteristics for bAVM ...
Shaozhi Zhao +24 more
doaj +1 more source
Quo vadis Radiomics? Bibliometric analysis of 10-year Radiomics journey
European Radiology, 2023 Abstract Objectives Radiomics is the high-throughput extraction of mineable and—possibly—reproducible quantitative imaging features from medical imaging. The aim of this work is to perform an unbiased bibliometric analysis on Radiomics 10 years after the first work became available, to highlight its status, pitfalls, and
Volpe S. +3 more
openaire +2 more sources
Frontiers in Oncology, 2021 PurposeWe aimed to explore potential confounders of prognostic radiomics signature predicting survival outcomes in clear cell renal cell carcinoma (ccRCC) patients and demonstrate how to control for them.Materials and MethodsPreoperative contrast ...
Lin Lu +9 more
doaj +1 more source
International Journal of Spine Surgery, 2023 Radiomics is an emerging approach to analyze clinical images with the purpose of revealing quantitative features that are unvisible to the naked eye. Radiomic features can be further combined with clinical data and genomic information to formulate prediction models using machine learning algorithms or manual statistical analysis.
Daniel, Alsoof +5 more
openaire +2 more sources
A Rapid Segmentation-Insensitive "Digital Biopsy" Method for Radiomic Feature Extraction: Method and Pilot Study Using CT Images of Non-Small Cell Lung Cancer. [PDF]
, 2016 Quantitative imaging approaches compute features within images' regions of interest. Segmentation is rarely completely automatic, requiring time-consuming editing by experts.
Echegaray, Sebastian +6 more
core +1 more source
Discovery Radiomics via Deep Multi-Column Radiomic Sequencers for Skin Cancer Detection [PDF]
, 2017 While skin cancer is the most diagnosed form of cancer in men and women, with more cases diagnosed each year than all other cancers combined, sufficiently early diagnosis results in very good prognosis and as such makes early detection crucial.
Shafiee, Mohammad Javad, Wong, Alexander
core +3 more sources
Multimodal Technologies and InteractionRadiomics involves extracting quantitative features from medical images, resulting in high-dimensional data. Unsupervised clustering has been used to discover patterns in radiomic features, potentially yielding hidden biological insights.
S. J. Pawan +6 more
doaj +1 more source
Frontiers in Neuroscience, 2021 PurposeTo investigate whether combining multiple radiomics signatures derived from the subregions of glioblastoma (GBM) can improve survival prediction of patients with GBM.MethodsIn total, 129 patients were included in this study and split into training
Yang Yang +8 more
doaj +1 more source
The transformational potential of molecular radiomics
Journal of Medical Radiation Sciences, 2023 Conventional radiomics in nuclear medicine involve hand‐crafted and computer‐assisted regions of interest. Recent developments in artificial intelligence (AI) have seen the emergence of AI‐augmented segmentation and extraction of lower order traditional ...
Geoffrey Currie +2 more
doaj +1 more source