Radiomics converts medical images into mineable data via a high-throughput extraction of
quantitative features used for clinical decision support. However, these radiomic features are …

Prostate cancer (PCa) is the most common worldwide diagnosed malignancy in male
population. The diagnosis, the identification of aggressive disease, and the post-treatment …

Radiomics research is rapidly growing in recent years, but more concerns on radiomics
reliability are also raised. This review attempts to update and overview the current status of …

Radiomics analysis is a powerful tool aiming to provide diagnostic and prognostic patient
information directly from images that are decoded into handcrafted features, comprising …

Objective Machine learning, deep learning, and artificial intelligence (AI) are terms that have
made their way into nearly all areas of medicine. In the case of medical imaging, these …

Radiomics is a method to mine large numbers of quantitative imaging features and develop
predictive models. It has shown exciting promise for improved cancer decision support from …

The reliability of radiomics features (RFs) is crucial for quantifying tumour heterogeneity. We
assessed the influence of imaging, segmentation, and processing conditions (quantization …

Image quantitation methods including quantitative MRI, multiparametric MRI, and radiomics
offer great promise for clinical use. However, many of these methods have limited clinical …

Simple Summary MRI radiomics shows promise in discriminating salivary gland tumors
(SGTs) but a consistent radiomics signature has not emerged, partly due to the multitude of …

Background The infrapatellar fat pad (IPFP) plays an important role in the incidence of knee
osteoarthritis (OA). Magnetic resonance (MR) signal heterogeneity of the IPFP is related to …