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Algorithm-based artifact reduction in patients with arms-down positioning in computed tomography.

Hiroki Kawashima¹, Katsuhiro Ichikawa¹, Tadanori Takata²

¹Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University, 5-11-80 Kodatsuno, Kanazawa 920-0942, Japan.

Physica Medica : PM : an International Journal Devoted to the Applications of Physics to Medicine and Biology : Official Journal of the Italian Association of Biomedical Physics (AIFB)

|December 13, 2019

Summary

This summary is machine-generated.

A new arm-artifact reduction algorithm (AAR) effectively reduces streak artifacts in computed tomography (CT) images of polytrauma patients. This novel method significantly improves image quality compared to iterative reconstruction techniques.

Keywords:

Artifact Computed tomography Image quality Polytrauma Reconstruction algorithm

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Area of Science:

Medical Imaging
Radiology
Image Processing

Background:

Arm-artifact is a common streak artifact in CT scans of polytrauma patients with arms down.
This artifact degrades diagnostic image quality.

Purpose of the Study:

To develop and evaluate a novel arm-artifact reduction algorithm (AAR) applied to projection data.
To compare AAR's effectiveness against existing iterative reconstruction (IR) techniques.

Main Methods:

A phantom study using a 16-row CT scanner compared AAR with two IR techniques (IR1, IR2).
Artifact reduction was quantified using a normalized artifact index (nAI).
Spatial resolution and image noise were assessed in phantom and clinical cases.

Main Results:

AAR significantly reduced nAI (84-87%) compared to filtered back projection, outperforming IR1 and IR2.
AAR preserved spatial resolution, unlike IR2 which caused blurring.
AAR significantly reduced image noise in clinical cases.

Conclusions:

The developed AAR is highly effective in reducing arm-artifacts in CT images.
AAR demonstrates superiority over current IR techniques for polytrauma imaging.
This algorithm is expected to enhance CT image quality for patients in arms-down positions.