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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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Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph

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Artifact reduction in truncated CT using Sinogram completion.

R Chityala¹, K R Hoffmann, S Rudin

¹Toshiba Stroke Research Center, Rm 445, Biomedical Research Building, State University of New York at Buffalo, 3435 Main Street, Buffalo, NY 14214.

Proceedings of Spie--The International Society for Optical Engineering

|September 28, 2011

Summary

This summary is machine-generated.

This study introduces a novel sinogram completion method to reduce CT truncation artifacts. The technique estimates out-of-region data, significantly improving reconstruction accuracy compared to traditional methods.

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Area of Science:

Medical Imaging
Image Reconstruction
Computational Science

Background:

Truncation of projection data in Computed Tomography (CT) leads to significant artifacts in image reconstruction.
These artifacts arise from the non-local nature of the Radon transform, complicating image analysis.

Purpose of the Study:

To present a method for reducing CT truncation artifacts.
To improve image reconstruction from incomplete projection data.

Main Methods:

A sinogram completion technique is proposed, estimating features outside the region of interest (ROI).
The method involves transforming the truncated sinogram into a Polar Representation (PR) image.
Completed sinogram data is generated by synthesizing sine curves in the PR image and reconstructing the image.

Main Results:

The completed reconstruction showed a 1.1% error compared to full field-of-view reconstruction.
This is a significant improvement over extrapolated-average reconstruction, which had a 3.3% error.
The proposed sinogram completion method effectively reduces truncation artifacts.

Conclusions:

Sinogram completion is a viable strategy for enhancing CT image reconstruction from truncated data.
The developed method offers a substantial improvement in accuracy and artifact reduction.
This technique has the potential to improve diagnostic quality in CT imaging.