Automated contrast-to-noise ratio analysis in chest CT: validation of an open-source segmentation approach

Q: What does this research mean for the field?

A fully automated, open-source segmentation approach provides an objective, reproducible, and accurate method for assessing contrast-to-noise ratio (CNR) to evaluate image quality in chest CT scans. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

Nikolas Beck; Giulia Baldini; Luca Salhöfer; René Hosch; Sebastian Zensen; Marcel Opitz; Denise Bos; Jannis Straus; Michael Forsting; Felix Nensa; Lale Umutlu; J. Haubold; Mathias Holtkamp

doi:10.1186/s13244-026-02263-y

April 7, 2026Insights into ImagingOpen Access

Automated contrast-to-noise ratio analysis in chest CT: validation of an open-source segmentation approach

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Key Points

To validate an open-source segmentation method for automated contrast-to-noise ratio (CNR) analysis in chest CT.
Developed an automated CNR assessment tool utilizing an open-source segmentation approach.
Conducted validation tests on chest CT images for accuracy and reproducibility.
Compared the automated measurements against established standards for image quality.
The automated approach yielded improved accuracy in evaluating contrast-to-noise ratios.
Segmentation adjustments significantly enhanced measurement precision.
The method demonstrates potential for standardized CT image quality assessments in both research and clinical settings.

Implication

Validation of an open-source segmentation approach improves image quality assessment in chest CT, suggesting enhanced analysis capabilities.

Abstract

Automated CNR assessment enables objective and reproducible evaluation of image quality in CTA and CTPA. Adjustments of the segmentation strategy can substantially improve the accuracy of automated measurements. The fully automated approach provides a foundation for standardized and scalable CT image quality analysis in research and clinical practice.

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Cite This Study

Beck et al. (2026) studied this question.

synapsesocial.com/papers/69d893626c1944d70ce0456c https://doi.org/10.1186/s13244-026-02263-y

View Full Paper

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Automated contrast-to-noise ratio analysis in chest CT: validation of an open-source segmentation approach

Key Points

Implication

Abstract

Discussion

Cite This Study

Automated contrast-to-noise ratio analysis in chest CT: validation of an open-source segmentation approach

Key Points

Implication

Abstract

Discussion

Cite This Study

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