Objectives In radiomics, different feature normalization methods, such as z-Score or Min–
Max, are currently utilized, but their specific impact on the model is unclear. We aimed to …

Background Radiomics extracts features from medical images more precisely and more
accurately than visual assessment. However, radiomics features are affected by CT scanner …

Purpose The purpose of this guideline is to provide comprehensive information on best
practices for robust radiomics analyses for both hand-crafted and deep learning-based …

Radiomics aims to support clinical decisions through its workflow, which is divided into:(i)
target identification and segmentation,(ii) feature extraction,(iii) feature selection, and (iv) …

Our purpose was to analyze the robustness and reproducibility of magnetic resonance
imaging (MRI) radiomic features. We constructed a multi-object fruit phantom to perform MRI …

Historically, medical imaging has been a qualitative or semi-quantitative modality. It is
difficult to quantify what can be seen in an image, and to turn it into valuable predictive …

Background Radiomics analyses has been proposed to interrogate the biology of tumour as
well as to predict/assess response to therapy in vivo. The objective of this work was to …

Medical imaging plays an indispensable role in evaluating, predicting, and monitoring a
range of medical conditions. Radiomics, a specialized branch of medical imaging, utilizes …

Background Radiomics and radiogenomics are two words that recur often in language of
radiologists, nuclear doctors and medical physicists especially in oncology field. Radiomics …

Quantitative analysis of medical images can provide objective tools for diagnosis,
prognostication, and disease monitoring. Radiomics refers to automated extraction of a large …