Universidad Complutense de Madrid
E-Prints Complutense

Use of the cross-correlation component of the multiscale structural similarity metric (R metric) for the evaluation of medical images

Impacto

Descargas

Último año

Prieto, G. y Guibelalde, E. y Chevalier, M. y Turrero, Agustín (2011) Use of the cross-correlation component of the multiscale structural similarity metric (R metric) for the evaluation of medical images. Medical physics, 38 (8). pp. 4512-4517. ISSN 0094-2405

[img] PDF
Restringido a Sólo personal autorizado del repositorio

1MB

URL Oficial: http://scitation.aip.org/content/aapm/journal/medphys/38/8/10.1118/1.3605634


URLTipo de URL
http://www.aip.org/Institución


Resumen

Purpose: 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.


Tipo de documento:Artículo
Palabras clave:CDMAM; image quality; mammography; model observer; MS-SSIM. EMTREE medical terms: algorithm; article; comparative study; computer assisted diagnosis; evaluation; female; human; image quality; mammography; methodology; observer variation; regression analysis; statistics. MeSH: Algorithms; Female; Humans; Mammography; Observer Variation; Phantoms, Imaging; Radiographic Image Interpretation, Computer-Assisted; Regression Analysis
Materias:Ciencias > Matemáticas > Estadística aplicada
Ciencias Biomédicas > Biología
Código ID:30855
Depositado:12 Jun 2015 10:34
Última Modificación:12 Jun 2015 10:34

Descargas en el último año

Sólo personal del repositorio: página de control del artículo