Tomography
Deep Learning–Based Reconstruction in Ultra-Low-Dose CT of the Ankle and Foot: A Comparative Study with Hybrid Iterative Reconstruction
By Chuluunbaatar Otgonbaatar, Jin Woo Kim, Sung-Jin Cha and 7 others.
Abstract
Objectives
To evaluate the quantitative and qualitative performance of ultra-low-dose CT with deep learning image reconstruction (DLR) compared to conventional hybrid iterative reconstruction (IR) in patients with ankle and foot fractures.
Methods
A total of 32 patients (mean age, 54 ± 16 years) with ankle and foot fractures were included in this retrospective study. All patients underwent ultra-low-dose CT imaging (effective dose, 0.86 ± 0.11 μSv), and the same CT raw data were reconstructed using both DLR and hybrid IR. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were quantitatively measured, and image sharpness was evaluated using a no-reference perceptual sharpness metric. Subjective image quality was assessed by a board-certified radiologist and an orthopedic surgeon using a five-point scale.
