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Computed Tomography

Computed Tomography

Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...

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Iterative Ring Artifact Removal Method for Helical Computed Tomography Scans.

Zsolt Adam Balogh¹, Tamas Huszar², Benedek Janos Kis²

¹From the Department of Mathematical Sciences, College of Science, United Arab Emirates University, Al Ain, United Arab Emirates.

Journal of Computer Assisted Tomography

|September 15, 2020

Summary

This summary is machine-generated.

A new statistical iterative ring removal (IRR) algorithm effectively corrects ring artifacts in computed tomography (CT) images caused by defective detector cells. This method accurately identifies and fixes false pixel values without introducing new artifacts.

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Area of Science:

Medical Imaging
Image Processing
Computational Science

Background:

Computed tomography (CT) detector element properties dynamically change due to temperature and irradiation variations.
These property changes can lead to false pixel values in sinograms, causing ring artifacts in reconstructed CT images.
Existing methods may struggle with low-contrast rings or introduce new artifacts.

Purpose of the Study:

To propose and evaluate a statistical-based iterative ring removal (IRR) algorithm for correcting ring artifacts in CT images.
To demonstrate the algorithm's effectiveness on clinical CT data with both artificial and real ring artifacts.
To assess the algorithm's ability to correct various types of ring artifacts without generating new image degradations.

Main Methods:

The study implemented a statistical-based iterative ring removal (IRR) algorithm.
The algorithm was tested on clinical CT data from two patients using a Mediso AnyScan SPECT/CT scanner.
Artificial and real ring artifacts, including single and band-like types, were used to evaluate the algorithm's performance.

Main Results:

The IRR algorithm successfully corrected both single and band-like ring artifacts, even those caused by multiple defective pixels.
The algorithm accurately detected and corrected only the periods with false pixel signals.
Significant reduction in ring artifacts was observed, including low-contrast rings, without introducing new artifacts.

Conclusions:

The statistical correction method efficiently detects and corrects false pixel values in projection data.
The IRR algorithm minimizes ring artifacts in reconstructed CT images without generating new artifacts.
The proposed algorithm demonstrates robustness and is less sensitive to parameter variations.