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Related Experiment Video

Updated: May 19, 2026

A Sectioning, Coring, and Image Processing Guide for High-Throughput Cortical Bone Sample Procurement and Analysis for Synchrotron Micro-CT

A Sectioning, Coring, and Image Processing Guide for High-Throughput Cortical Bone Sample Procurement and Analysis for Synchrotron Micro-CT

Published on: June 12, 2020

Bone-induced streak artifact suppression in sparse-view CT image reconstruction.

Seung Oh Jin¹, Jae Gon Kim, Soo Yeol Lee

¹Korea Electrotechnology Research Institute, Seoul, Korea.

Biomedical Engineering Online

|August 4, 2012

Summary

This study presents a novel method to reduce streak artifacts in sparse-view CT imaging caused by bone. The technique effectively suppresses these artifacts, improving image quality for better readability.

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Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin

Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin

Published on: March 14, 2018

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Last Updated: May 19, 2026

A Sectioning, Coring, and Image Processing Guide for High-Throughput Cortical Bone Sample Procurement and Analysis for Synchrotron Micro-CT

A Sectioning, Coring, and Image Processing Guide for High-Throughput Cortical Bone Sample Procurement and Analysis for Synchrotron Micro-CT

Published on: June 12, 2020

Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin

Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin

Published on: March 14, 2018

Area of Science:

Medical Imaging
Image Reconstruction
Computational Imaging

Background:

Sparse-view CT imaging often produces streak artifacts around bony structures, hindering image interpretation.
Existing compressed sensing (CS) and total variation (TV) minimization methods reduce artifacts but leave residual issues.
A new method is introduced to specifically address bone-induced streak artifacts in CS-based reconstruction.

Purpose of the Study:

To develop and validate a novel technique for reducing bone-induced streak artifacts in sparse-view CT imaging.
To improve the image quality and readability compromised by residual artifacts in CS-based reconstruction.

Main Methods:

Identify high-intensity bony regions from filtered backprojection (FBP) images.
Calculate and subtract bone-only sinograms from measured sinograms before CS reconstruction.
Reconstruct soft tissue images, then combine with identified bone regions for a second CS reconstruction using the combined image as an initial condition.

Main Results:

Visual inspection revealed significantly reduced streak artifacts compared to conventional CS methods.
Quantitative evaluations using relative mean square error and total variation confirmed the proposed method's superiority.
The reconstructed images demonstrated improved clarity and reduced artifact presence.

Conclusions:

The proposed method effectively suppresses streak artifacts originating from bony structures in sparse-view CT.
This technique enhances the diagnostic value of sparse-view CT imaging by improving image quality.