Quantifying effects of post-processing with visual grading regression

Örjan Smedby; Mats Fredrikson; Jakob De Geer; Michael Sandborg

doi:10.1117/12.912321

6 March 2012 Quantifying effects of post-processing with visual grading regression

Örjan Smedby, Mats Fredrikson, Jakob De Geer, Michael Sandborg

Proceedings Volume 8318, Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment; 83181N (2012) https://doi.org/10.1117/12.912321
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

For optimization and evaluation of image quality, one can use visual grading experiments, where observers rate some aspect of image quality on an ordinal scale. To take into account the ordinal character of the data, ordinal logistic regression is used in the statistical analysis, an approach known as visual grading regression (VGR). In the VGR model one may include factors such as imaging parameters and post-processing procedures, in addition to patient and observer identity. In a single-image study, 9 radiologists graded 24 cardiac CTA images acquired with ECG-modulated tube current using standard settings (310 mAs), reduced dose (62 mAs) and reduced dose after post-processing. Image quality was assessed using visual grading with five criteria, each with a five-level ordinal scale from 1 (best) to 5 (worst). The VGR model included one term estimating the dose effect (log of mAs setting) and one term estimating the effect of postprocessing. The model predicted that 115 mAs would be required to reach an 80% probability of a score of 1 or 2 for visually sharp reproduction of the heart without the post-processing filter. With the post-processing filter, the corresponding figure would be 86 mAs. Thus, applying the post-processing corresponded to a dose reduction of 25%. For other criteria, the dose-reduction was estimated to 16-26%. Using VGR, it is thus possible to quantify the potential for dose-reduction of post-processing filters.

Citation Download Citation

Örjan Smedby, Mats Fredrikson, Jakob De Geer, and Michael Sandborg "Quantifying effects of post-processing with visual grading regression", Proc. SPIE 8318, Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment, 83181N (6 March 2012); https://doi.org/10.1117/12.912321

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KEYWORDS

Visualization

Image quality

Statistical analysis

Image filtering

Heart

Computed tomography

Digital filtering

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