How does intelligent noise reduction software influence the image quality in pelvic digital radiography: A phantom study.

Introduction: This study aims to evaluate the effects of a novel noise reduction software (INR, Canon Europe, Amsterdam, NL) on image quality (IQ) in Digital Radiography (DR) pelvic phantom images.

Methods: In total, 53 pelvic phantom images and 360 technical images of a Contrast Detail Radiography phantom (CDRAD) were collected, including 8 different exposure levels (between 0.8 and 40 mAs at 70 kV) and 6 intensities of INR (ranging from settings 0-10).

Verb Vocabulary Supports Event Probability Use in Developmental Language Disorder.

Purpose: Children with developmental language disorder (DLD) tend to interpret noncanonical sentences like passives using event probability (EP) information regardless of structure (e.g., by interpreting "The dog was chased by the squirrel" as "The dog chased the squirrel").

Can advanced edge enhancement software improve image quality to visualise tubes, catheters and wires in digital chest radiographs?

Introduction: This study aimed to test whether Advanced Edge Enhancement (AEE) software could improve the localisation of tubes, catheters or wires, while also affecting the overall image quality in chest x-rays (CXR).

Methods: In total, 50 retrospective CXRs were included. All images were obtained utilising the Canon X-ray system (CANON/Arcoma Precision T3 DR System, Canon Europe, Amsterdam, NL) with a CXDI-810C wireless detector.

COMPARISON OF CONVENTIONAL HAND EXAMINATION ON SIX OPTIMISED DR SYSTEMS.

The purpose of this study was to investigate the challenges in comparing digital radiography (DR) systems from different vendors for various combinations of exposure factors in posterior-anterior hand radiographs. Image quality was evaluated for a range of tube voltages and tube current-time products using a technical contrast-detail (CDRAD) phantom and an anthropomorphic hand phantom. 900 technical CDRAD images were analysed providing quality figures of merit (IQFinv) and two experienced reporting radiographers using visual grading analysis (VGA) scored 108 anthropomorphic images.