TU‐E‐201B‐07: Image Noise and Radiation Dose Reduction in Spectral CT

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Purpose: Spectral (multiple energy) CT can characterize material composition using the x‐ray spectral information. However, image noise and radiation dose is a concern as photons are distributed into multiple energy bins. Therefore, the intrinsic trade‐off between number of energy bins and photon numbers in each bin results in either too noisy images, or too high radiation dose. The purpose of this study is to break this trade‐off and to reduce noise and/or radiation dose in spectral CT. Method and Materials: A semi‐anthropomorphic thoracic phantom was scanned with multiple energies (80,100, 120 and 140 kVps) on a dual source CT scanner. Images were reconstructed at each beam‐energy separately using commercial software. The reconstructed images were processed wtih the Highly Constrained Back‐Projection (HYPR) algorithm using the averaged image of all 4 kVp scans as the composite image. CT numbers and noise were measured inside three circular ROIs representing calcium, water, and soft tissue. Noise and dose reduction using HYPR compared with commercial software was calculated. Results: The same CT numbers were obtained using both algorithms while approximately 50% of noise reduction was achieved using HYPR. Based upon the relationship between noise and radiation dose, this was equivalent to 4 times dose reduction given the same image noise. These results could be interpreted as noise reduction given the same radiation dose, dose reduction given the same image noise, or a combination of these two. Conclusion: We have presented a method to reduce image noise and/or radiation dose in spectral CT. Using HYPR, images at each individual energy bin have SNR similar as the composite image which uses all x‐ray photons. This breaks the tradeoff between number of energy bins and number of photons in each bin. Therefore, the intrinsic problem of excessive noise and/or radiation dose in spectral CT has been addressed.

Original languageEnglish (US)
Pages (from-to)3408
Number of pages1
JournalMedical Physics
Volume37
Issue number6
DOIs
StatePublished - 2010

Fingerprint

Noise
Radiation
Photons
Software
X-Rays
Thorax
Calcium
Water

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

Cite this

@article{57b33cd5e00e4a068446ca62420f83db,
title = "TU‐E‐201B‐07: Image Noise and Radiation Dose Reduction in Spectral CT",
abstract = "Purpose: Spectral (multiple energy) CT can characterize material composition using the x‐ray spectral information. However, image noise and radiation dose is a concern as photons are distributed into multiple energy bins. Therefore, the intrinsic trade‐off between number of energy bins and photon numbers in each bin results in either too noisy images, or too high radiation dose. The purpose of this study is to break this trade‐off and to reduce noise and/or radiation dose in spectral CT. Method and Materials: A semi‐anthropomorphic thoracic phantom was scanned with multiple energies (80,100, 120 and 140 kVps) on a dual source CT scanner. Images were reconstructed at each beam‐energy separately using commercial software. The reconstructed images were processed wtih the Highly Constrained Back‐Projection (HYPR) algorithm using the averaged image of all 4 kVp scans as the composite image. CT numbers and noise were measured inside three circular ROIs representing calcium, water, and soft tissue. Noise and dose reduction using HYPR compared with commercial software was calculated. Results: The same CT numbers were obtained using both algorithms while approximately 50{\%} of noise reduction was achieved using HYPR. Based upon the relationship between noise and radiation dose, this was equivalent to 4 times dose reduction given the same image noise. These results could be interpreted as noise reduction given the same radiation dose, dose reduction given the same image noise, or a combination of these two. Conclusion: We have presented a method to reduce image noise and/or radiation dose in spectral CT. Using HYPR, images at each individual energy bin have SNR similar as the composite image which uses all x‐ray photons. This breaks the tradeoff between number of energy bins and number of photons in each bin. Therefore, the intrinsic problem of excessive noise and/or radiation dose in spectral CT has been addressed.",
author = "Shuai Leng and McCollough, {Cynthia H} and Fletcher, {Joel Garland} and Lifeng Yu and C. Mistretta",
year = "2010",
doi = "10.1118/1.3469317",
language = "English (US)",
volume = "37",
pages = "3408",
journal = "Medical Physics",
issn = "0094-2405",
publisher = "AAPM - American Association of Physicists in Medicine",
number = "6",

}

TY - JOUR

T1 - TU‐E‐201B‐07

T2 - Image Noise and Radiation Dose Reduction in Spectral CT

AU - Leng, Shuai

AU - McCollough, Cynthia H

AU - Fletcher, Joel Garland

AU - Yu, Lifeng

AU - Mistretta, C.

PY - 2010

Y1 - 2010

N2 - Purpose: Spectral (multiple energy) CT can characterize material composition using the x‐ray spectral information. However, image noise and radiation dose is a concern as photons are distributed into multiple energy bins. Therefore, the intrinsic trade‐off between number of energy bins and photon numbers in each bin results in either too noisy images, or too high radiation dose. The purpose of this study is to break this trade‐off and to reduce noise and/or radiation dose in spectral CT. Method and Materials: A semi‐anthropomorphic thoracic phantom was scanned with multiple energies (80,100, 120 and 140 kVps) on a dual source CT scanner. Images were reconstructed at each beam‐energy separately using commercial software. The reconstructed images were processed wtih the Highly Constrained Back‐Projection (HYPR) algorithm using the averaged image of all 4 kVp scans as the composite image. CT numbers and noise were measured inside three circular ROIs representing calcium, water, and soft tissue. Noise and dose reduction using HYPR compared with commercial software was calculated. Results: The same CT numbers were obtained using both algorithms while approximately 50% of noise reduction was achieved using HYPR. Based upon the relationship between noise and radiation dose, this was equivalent to 4 times dose reduction given the same image noise. These results could be interpreted as noise reduction given the same radiation dose, dose reduction given the same image noise, or a combination of these two. Conclusion: We have presented a method to reduce image noise and/or radiation dose in spectral CT. Using HYPR, images at each individual energy bin have SNR similar as the composite image which uses all x‐ray photons. This breaks the tradeoff between number of energy bins and number of photons in each bin. Therefore, the intrinsic problem of excessive noise and/or radiation dose in spectral CT has been addressed.

AB - Purpose: Spectral (multiple energy) CT can characterize material composition using the x‐ray spectral information. However, image noise and radiation dose is a concern as photons are distributed into multiple energy bins. Therefore, the intrinsic trade‐off between number of energy bins and photon numbers in each bin results in either too noisy images, or too high radiation dose. The purpose of this study is to break this trade‐off and to reduce noise and/or radiation dose in spectral CT. Method and Materials: A semi‐anthropomorphic thoracic phantom was scanned with multiple energies (80,100, 120 and 140 kVps) on a dual source CT scanner. Images were reconstructed at each beam‐energy separately using commercial software. The reconstructed images were processed wtih the Highly Constrained Back‐Projection (HYPR) algorithm using the averaged image of all 4 kVp scans as the composite image. CT numbers and noise were measured inside three circular ROIs representing calcium, water, and soft tissue. Noise and dose reduction using HYPR compared with commercial software was calculated. Results: The same CT numbers were obtained using both algorithms while approximately 50% of noise reduction was achieved using HYPR. Based upon the relationship between noise and radiation dose, this was equivalent to 4 times dose reduction given the same image noise. These results could be interpreted as noise reduction given the same radiation dose, dose reduction given the same image noise, or a combination of these two. Conclusion: We have presented a method to reduce image noise and/or radiation dose in spectral CT. Using HYPR, images at each individual energy bin have SNR similar as the composite image which uses all x‐ray photons. This breaks the tradeoff between number of energy bins and number of photons in each bin. Therefore, the intrinsic problem of excessive noise and/or radiation dose in spectral CT has been addressed.

UR - http://www.scopus.com/inward/record.url?scp=80052424187&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80052424187&partnerID=8YFLogxK

U2 - 10.1118/1.3469317

DO - 10.1118/1.3469317

M3 - Article

AN - SCOPUS:80052424187

VL - 37

SP - 3408

JO - Medical Physics

JF - Medical Physics

SN - 0094-2405

IS - 6

ER -