Over the last decade there has been an extensive evolution in the Artificial Intelligence (AI)
field. Modern radiation oncology is based on the exploitation of advanced computational …

Simple Summary The two most common cross-sectional imaging modalities, computed
tomography (CT) and magnetic resonance imaging (MRI), have shown enormous utility in …

Despite technological and medical advances, the detection, interpretation, and treatment of
cancer based on imaging data continue to pose significant challenges. These include inter …

Compared to computed tomography (CT), magnetic resonance imaging (MRI) is more
sensitive to acute ischemic stroke lesion. However, MRI is time-consuming, expensive, and …

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 …

Abstract Background and Objectives Artificial intelligence (AI) models trained on multi-
centric and multi-device studies can provide more robust insights and research findings …

Despite technological and medical advances, the detection, interpretation, and treatment of
cancer based on imaging data continue to pose significant challenges. These include high …

Background Studies on computed tomography (CT) synthesis based on magnetic
resonance imaging (MRI) have mainly focused on pixel‐wise consistency, but the texture …

Aim The rate of physiological bone remodelling (PBR) occurring after implant placement has
been associated with the later onset of progressive bone loss and peri‐implantitis, leading to …

Background As a means to extract biomarkers from medical imaging, radiomics has
attracted increased attention from researchers. However, reproducibility and performance of …