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Thoracic low-dose CT image processing using an artifact suppressed large-scale nonlocal means.

Yang Chen¹, Zhou Yang, Yining Hu

¹Laboratory of Image Science and Technology, Southeast University, Nanjing, People's Republic of China. chenyang.list@seu.edu.cn

Physics in Medicine and Biology

|April 17, 2012

Summary

This study introduces a novel method to reduce noise and artifacts in low-dose CT scans of the chest. The artifact suppressed large-scale nonlocal means technique improves image quality for better medical diagnoses.

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Area of Science:

Medical Imaging
Radiology
Image Processing

Background:

Minimizing patient x-ray exposure is crucial in computed tomography (CT).
Thoracic low-dose CT (LDCT) images suffer from noise and streak artifacts due to high-attenuation tissues.
Artifacts are difficult to distinguish from normal tissue information in LDCT.

Purpose of the Study:

To develop a method for suppressing noise and artifacts in thoracic LDCT images.
To improve the quality of thoracic LDCT data for enhanced diagnostic accuracy.

Main Methods:

A two-step processing scheme named 'artifact suppressed large-scale nonlocal means' was developed.
The method utilizes specific scale and direction properties to differentiate artifacts from image structures.
Parallel implementation was used to accelerate the processing speed by over 100 times.

Main Results:

The proposed method effectively suppresses both noise and artifacts in thoracic LDCT images.
Phantom and patient CT images demonstrated the efficacy of the technique.
Comparative analyses confirmed significant improvements in image quality.

Conclusions:

The artifact suppressed large-scale nonlocal means method is effective for thoracic LDCT.
This technique offers a viable solution for enhancing image quality while reducing radiation exposure.
The parallel implementation ensures efficient processing for clinical applications.