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A metal artifact reduction method for a dental CT based on adaptive local thresholding and prior image generation

Overview of attention for article published in BioMedical Engineering OnLine, November 2016
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Title
A metal artifact reduction method for a dental CT based on adaptive local thresholding and prior image generation
Published in
BioMedical Engineering OnLine, November 2016
DOI 10.1186/s12938-016-0240-8
Pubmed ID
Authors

Mohamed A. A. Hegazy, Min Hyoung Cho, Soo Yeol Lee

Abstract

Metal artifacts appearing as streaks and shadows often compromise readability of computed tomography (CT) images. Particularly in a dental CT in which high resolution imaging is crucial for precise preparation of dental implants or orthodontic devices, reduction of metal artifacts is very important. However, metal artifact reduction algorithms developed for a general medical CT may not work well in a dental CT since teeth themselves also have high attenuation coefficients. To reduce metal artifacts in dental CT images, we made prior images by weighted summation of two images: one, a streak-reduced image reconstructed from the metal-region-modified projection data, and the other a metal-free image reconstructed from the original projection data followed by metal region deletion. To make the streak-reduced image, we precisely segmented the metal region based on adaptive local thresholding, and then, we modified the metal region on the projection data using linear interpolation. We made forward projection of the prior image to make the prior projection data. We replaced the pixel values at the metal region in the original projection data with the ones taken from the prior projection data, and then, we finally reconstructed images from the replaced projection data. To validate the proposed method, we made computational simulations and also we made experiments on teeth phantoms using a micro-CT. We compared the results with the ones obtained by the fusion prior-based metal artifact reduction (FP-MAR) method. In the simulation studies using a bilateral prostheses phantom and a dental phantom, the proposed method showed a performance similar to the FP-MAR method in terms of the edge profile and the structural similarity index when an optimal global threshold was chosen for the FP-MAR method. In the imaging studies of teeth phantoms, the proposed method showed a better performance than the FP-MAR method in reducing the streak artifacts without introducing any contrast anomaly. The simulation and experimental imaging studies suggest that the proposed method can be used for reducing metal artifacts in dental CT images.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 54 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 9 17%
Unspecified 8 15%
Student > Ph. D. Student 7 13%
Other 4 7%
Researcher 4 7%
Other 9 17%
Unknown 13 24%
Readers by discipline Count As %
Medicine and Dentistry 14 26%
Engineering 10 19%
Unspecified 8 15%
Physics and Astronomy 2 4%
Nursing and Health Professions 1 2%
Other 5 9%
Unknown 14 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 November 2016.
All research outputs
#18,480,433
of 22,899,952 outputs
Outputs from BioMedical Engineering OnLine
#563
of 822 outputs
Outputs of similar age
#235,226
of 311,298 outputs
Outputs of similar age from BioMedical Engineering OnLine
#7
of 10 outputs
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So far Altmetric has tracked 822 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
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