A signal detection model for quantifying overregularization in nonlinear image reconstruction-Reference-Cited by-同舟云学术

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A signal detection model for quantifying overregularization in nonlinear image reconstruction

Published:2021-06-25 Issue:10 Volume:48 Page:6312-6323
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Sidky Emil Y.¹,Phillips John Paul¹,Zhou Weimin²,Ongie Greg³,Cruz‐Bastida Juan P.¹,Reiser Ingrid S.¹,Anastasio Mark A.²,Pan Xiaochuan¹

Affiliation:

1. Department of Radiology The University of Chicago 5841 S. Maryland Ave. Chicago IL60637USA

2. Department of Bioengineering University of Illinois at Urbana‐Champaign 1406 W. Green St. Urbana IL61801USA

3. Department of Mathematical and Statistical Sciences Marquette University 1313 W. Wisconsin Ave. Milwaukee WI53233USA

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.14703

Reference30 articles.

1. Statistical image reconstruction for polyenergetic X-ray computed tomography

2. Strategies for Reducing Radiation Dose in CT

3. Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization

4. Prior image constrained compressed sensing (PICCS): A method to accurately reconstruct dynamic CT images from highly undersampled projection data sets

5. Improved total variation-based CT image reconstruction applied to clinical data

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1. Visualization of the distortion induced by nonlinear noise reduction in computed tomography;Journal of Medical Imaging;2023-06-15

2. Addressing CT metal artifacts using photon‐counting detectors and one‐step spectral CT image reconstruction;Medical Physics;2022-04-05

3. Complex Relationship Between Artificial Intelligence and CT Radiation Dose;Academic Radiology;2021-11

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