The increasing use of computed tomography (CT) and cone beam computed tomography
(CBCT) in oral and maxillofacial imaging has driven the development of deep learning and …

Introduction The advent of image-guided radiation therapy (IGRT) has recently changed the
workflow of radiation treatments by ensuring highly collimated treatments. Artificial …

Background In radiomics studies, differences in the volume of interest (VOI) are often
inevitable and may confound the extracted features. We aimed to correct this confounding …

Simple Summary This study is the first to evaluate the impact of contouring differences on
radiomics analysis in preclinical CBCT scans. We found that the variation in quantitative …

Neurodegenerative diseases refer to degenerative diseases of the nervous system caused
by neuronal degeneration and apoptosis. Usually, the onset of the disease is insidious, and …

“Just Accepted” papers have undergone full peer review and have been accepted for
publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout …

Objectives Robustness of radiomic features in physiological tissue is an important
prerequisite for quantitative analysis of tumor biology and response assessment. In contrast …

Objectives: This study aims to determine the reproducibility and location-stability of cone-
beam computed tomography (CBCT) radiomic features. Methods: Centrifugal tubes with six …

Background and purpose Radiomics features derived from medical images have the
potential to act as imaging biomarkers to improve diagnosis and predict treatment response …

Diffusion-weighted imaging (DWI) combined with radiomics can aid in the differentiation of
breast lesions. Segmentation characteristics, however, might influence radiomic features. To …