6533b821fe1ef96bd127b075
RESEARCH PRODUCT
Advantages of fitting contrast curves using logistic function: a technical note.
Dan BrüllmannAnna M. Sachssubject
Mean squared errorComputer scienceContrast (statistics)Image processingRadiography Dental DigitalPathology and Forensic MedicineRadiographic Image EnhancementLogistic ModelsGoodness of fitStatisticsLine (geometry)Image Processing Computer-AssistedHumansRadiology Nuclear Medicine and imagingDentistry (miscellaneous)SurgeryRadiographic Image EnhancementX-Ray Intensifying ScreensOral SurgeryLogistic functionMATLABcomputerAlgorithmAlgorithmscomputer.programming_languagedescription
Objective The aim of this article is to demonstrate how the contrast properties of an imaging system can be ideally fitted with the use of stripe patterns and the logistic function. Study Design Stripe patterns with defined amounts of line pairs (lp/mm) per mm (10-20 lp/mm) were recorded with the use of digital photostimulable storage phosphor. Scan data and normalized image data were analyzed with the use of ImageJ and MatLab to calculate different contrast curves. Results For original scan data, the goodness of fit was 0.0000019 (sum of squared error [SSE]). The R-square was 0.9998. For normalized data the goodness of fit was 0.0007 (SSE) and the R-square 0.998. An amount of 50% contrast could be calculated to be found on 11.67 lp/mm in normalized images. Conclusions This article addresses a potentially new approach to compare digital x-ray modalities using a direct assessment of a known technical target.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2013-03-01 | Oral surgery, oral medicine, oral pathology and oral radiology |