Prieto Renieblas, GabrielGuibelalde Del Castillo, EduardoChevalier Del Río, MargaritaTurrero Nogués, Agustín2023-06-202023-06-202011-08Prieto, G., Cguibelalde, E., Chevalier Del Río, M. & Turrero Nogués, A. et al. «Use of the Cross‐correlation Component of the Multiscale Structural Similarity Metric (R* Metric) for the Evaluation of Medical Images». Medical Physics, vol. 38, n.o 8, agosto de 2011, pp. 4512-17. DOI.org (Crossref), https://doi.org/10.1118/1.3605634.0094-240510.1118/1.3605634https://hdl.handle.net/20.500.14352/44637Purpose: The aim of the present work is to analyze the potential of the cross-correlation component of the multiscale structural similarity metric (R*) to predict human performance in detail detection tasks closely related with diagnostic x-ray images. To check the effectiveness of R, the authors have initially applied this metric to a contrast detail detection task. Methods: Threshold contrast visibility using the R* metric was determined for two sets of images of a contrast-detail phantom (CDMAM). Results from R and human observers were compared as far as the contrast threshold was concerned. A comparison between the R* metric and two algorithms currently used to evaluate CDMAM images was also performed. Results: Similar trends for the CDMAM detection task of human observers and R* were found in this study. Threshold contrast visibility values using R* are statistically indistinguishable from those obtained by human observers (F-test statistics: p > 0.05). Conclusions: These results using R* show that it could be used to mimic human observers for certain tasks, such as the determination of contrast detail curves in the presence of uniform random noise backgrounds. The R* metric could also outperform other metrics and algorithms currently used to evaluate CDMAM images and can automate this evaluation task.engjournal articlehttps//doi.org/10.1118/1.3605634http://scitation.aip.org/content/aapm/journal/medphys/38/8/10.1118/1.3605634http://www.aip.org/restricted access51-76CDMAMImage qualityMammographyModel observerMS-SSIM. EMTREE medical terms: algorithmArticleComparative studyComputer assisted diagnosisEvaluationFemaleHumanMethodologyObserver variationRegression analysisStatisticsMeSH: AlgorithmsFemaleHumansMammographyObserver VariationPhantomsImagingRadiographic Image InterpretationComputer-AssistedRegression AnalysisEstadística aplicadaBiología24 Ciencias de la Vida