Summary
We compared four unsharp mask filtering algorithms for storage phosphor chest radiographs (1744 x 2144 x 10bit matrix) and conventional screen/film images (FR) in the detection of three types of simulated lung disease: nodules, fine lines and micronodular opacities. Unsharp mask filtering was performed with filter kernels that were “small” (kernel length = 1.4 mm, SRS), “medium” (5 mm, SRm, current industry default), “large” (2.5 cm, SRI), and “ultralarge” (7 cm, SRuI). In a ROC study, lesion detection was estimated by ROC areas (AZ), and significance of differences was tested by analysis of variance (p < 0.05).
In the detection of nodules, FR, SRuI, and SRI were superior to SRm and SRS. In the detection of lines, FR was only superior to SRuI; all other SR versions were equivalent to FR. In the detection of micronodular opacities, all SR algorithms were inferior to FR. However, SRm and SRI performed better than SRS.
Unsharp mask filtering with large kernels (SRI) seems to be the most appropriate algorithm to simultaneously match linear, nodular and micronodular structures.
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© 1991 Springer-Verlag Berlin Heidelberg
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Prokop, M., Schaefer, C., Oestmann, J.W., Meschede, A., Reichelt, S., Galanski, M. (1991). Optimal Parameters for Unsharp Mask Filtering of Digital Chest Radiographs. In: Lemke, H.U., Rhodes, M.L., Jaffe, C.C., Felix, R. (eds) Computer Assisted Radiology / Computergestützte Radiologie. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-00807-2_24
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DOI: https://doi.org/10.1007/978-3-662-00807-2_24
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