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 …

Quantitative analysis of tumour characteristics based on medical imaging is an emerging
field of research. In recent years, quantitative imaging features derived from CT, positron …

In the past decade, the field of medical image analysis has grown exponentially, with an
increased number of pattern recognition tools and an increase in data set sizes. These …

Purpose To investigate the value of T2-weighted–based radiomics compared with
qualitative assessment at T2-weighted imaging and diffusion-weighted (DW) imaging for …

The increasing use of biomarkers in cancer have led to the concept of personalized
medicine for patients. Personalized medicine provides better diagnosis and treatment …

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 …

In this study we assessed the repeatability of radiomics features on small prostate tumors
using test-retest Multiparametric Magnetic Resonance Imaging (mpMRI). The premise of …

Objectives To evaluate the recommendations for multiparametric prostate MRI (mp-MRI)
interpretation introduced in the recently updated Prostate Imaging Reporting and Data …

Purpose To compare biparametric contrast-free radiomic machine learning (RML), mean
apparent diffusion coefficient (ADC), and radiologist assessment for characterization of …

With this review, we aimed to provide a synopsis of recently proposed applications of
machine learning (ML) in radiology focusing on prostate magnetic resonance imaging (MRI) …