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Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
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Generalized SDNR analysis based on signal and noise power.
P Monnin1, S Gnesin1, F R Verdun1
1Institute of Radiation Physics (IRA), Lausanne University Hospital (CHUV) and University of Lausanne, Rue du Grand-Pré 1, 1007 Lausanne, Switzerland.
Summary
A new generalized signal-difference-to-noise ratio (SDNRg) method accurately measures image quality for non-uniform objects. This advanced SDNR analysis improves accuracy for small objects, outperforming the standard SDNR method.
Area of Science:
- Medical imaging physics
- Image quality assessment
- Radiography and mammography
Background:
- Standard signal-difference-to-noise ratio (SDNR) analysis is limited to objects with sharp, flat tops.
- This limitation restricts its application in analyzing non-uniform or small objects in medical imaging.
Purpose of the Study:
- To develop and validate a generalized expression for SDNR (SDNRg) applicable to a wider range of object types.
- To compare the accuracy of SDNRg with the standard SDNR (SDNRst) for various object shapes and sizes.
Main Methods:
- Developed a generalized SDNR expression (SDNRg) using signal power from a region of interest encompassing the object.
- Simulated ideal discs of varying sizes in a noisy background to compare SDNRg and SDNRst.
- Applied both methods to radiography images of phantoms with microcalcification-like objects, Gaussian-distributed hemispheric objects, and mammography quality control images.
Main Results:
- SDNRg showed higher accuracy than SDNRst for small simulated discs (<20 pixels), with SDNRg within 26% of truth vs. 58% for SDNRst.
- For Gaussian details, SDNRg was 20-45% higher than SDNRst, depending on object thickness.
- SDNRg results were within 1.7% of SDNRst for mammography QC images.
Conclusions:
- The generalized SDNR (SDNRg) method expands the applicability of SDNR analysis to non-uniform signals where contrast measurement is unsuitable.
- SDNRg offers improved accuracy, particularly for small objects, compared to the standard SDNR method.
- This generalized approach enhances objective image quality assessment in medical imaging.
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