Improving image quality and diagnostic performance using deep learning image reconstruction in 100-kVp CT enterography for patients with wide-range body mass index.
Journal:
European journal of radiology
Published Date:
Aug 1, 2025
Abstract
OBJECTIVE: To assess the clinical value of the deep learning image reconstruction (DLIR) algorithm compared with conventional adaptive statistical iterative reconstruction-Veo (ASiR-V) in image quality, diagnostic confidence, and intestinal lesion detection in 100-kVp CT enterography (CTE) for patients with wide-range body mass index (BMI).
Authors
Keywords
Adult
Aged
Aged, 80 and over
Algorithms
Body Mass Index
Deep Learning
Female
Humans
Intestinal Diseases
Male
Middle Aged
Quality Improvement
Radiographic Image Interpretation, Computer-Assisted
Reproducibility of Results
Retrospective Studies
Sensitivity and Specificity
Signal-To-Noise Ratio
Tomography, X-Ray Computed