PURPOSE: To assess the effect of noise reduction filters on detection and characterization of lesions on low-radiation-dose abdominal computed tomographic (CT) images. MATERIALS AND METHODS: Low-dose CT images of abdominal lesions in 19 consecutive patients (11 women, eight men; age range, 32-78 years) were obtained at reduced tube currents (120-144 mAs). These baseline low-dose CT images were postprocessed with six noise reduction filters; the resulting postprocessed images were then randomly assorted with baseline images. Three radiologists performed independent evaluation of randomized images for presence, number, margins, attenuation, conspicuity, calcification, and enhancement of lesions, as well as image noise. Side-by-side comparison of baseline images with postprocessed images was performed by using a five-point scale for assessing lesion conspicuity and margins, image noise, beam hardening, and diagnostic acceptability. Quantitative noise and contrast-to-noise ratio were obtained for all liver lesions. Statistical analysis was performed by using the Wilcoxon signed rank test, Student t test, and kappa test of agreement. RESULTS: Significant reduction of noise was observed in images postprocessed with filter F compared with the noise in baseline nonfiltered images (P =.004). Although the number of lesions seen on baseline images and that seen on postprocessed images were identical, lesions were less conspicuous on postprocessed images than on baseline images. A decrease in quantitative image noise and contrast-to-noise ratio for liver lesions was noted with all noise reduction filters. There was good interobserver agreement (kappa = 0.7). CONCLUSION: Although the use of currently available noise reduction filters improves image noise and ameliorates beam-hardening artifacts at low-dose CT, such filters are limited by a compromise in lesion conspicuity and appearance in comparison with lesion conspicuity and appearance on baseline low-dose CT images. Copyright RSNA, 2004
PURPOSE: To assess the effect of noise reduction filters on detection and characterization of lesions on low-radiation-dose abdominal computed tomographic (CT) images. MATERIALS AND METHODS: Low-dose CT images of abdominal lesions in 19 consecutive patients (11 women, eight men; age range, 32-78 years) were obtained at reduced tube currents (120-144 mAs). These baseline low-dose CT images were postprocessed with six noise reduction filters; the resulting postprocessed images were then randomly assorted with baseline images. Three radiologists performed independent evaluation of randomized images for presence, number, margins, attenuation, conspicuity, calcification, and enhancement of lesions, as well as image noise. Side-by-side comparison of baseline images with postprocessed images was performed by using a five-point scale for assessing lesion conspicuity and margins, image noise, beam hardening, and diagnostic acceptability. Quantitative noise and contrast-to-noise ratio were obtained for all liver lesions. Statistical analysis was performed by using the Wilcoxon signed rank test, Student t test, and kappa test of agreement. RESULTS: Significant reduction of noise was observed in images postprocessed with filter F compared with the noise in baseline nonfiltered images (P =.004). Although the number of lesions seen on baseline images and that seen on postprocessed images were identical, lesions were less conspicuous on postprocessed images than on baseline images. A decrease in quantitative image noise and contrast-to-noise ratio for liver lesions was noted with all noise reduction filters. There was good interobserver agreement (kappa = 0.7). CONCLUSION: Although the use of currently available noise reduction filters improves image noise and ameliorates beam-hardening artifacts at low-dose CT, such filters are limited by a compromise in lesion conspicuity and appearance in comparison with lesion conspicuity and appearance on baseline low-dose CT images. Copyright RSNA, 2004
Authors: A Korn; M Fenchel; B Bender; S Danz; T K Hauser; D Ketelsen; T Flohr; C D Claussen; M Heuschmid; U Ernemann; H Brodoefel Journal: AJNR Am J Neuroradiol Date: 2011-10-27 Impact factor: 3.825
Authors: Sebastian T Schindera; Reto Treier; Gabriel von Allmen; Claude Nauer; Philipp R Trueb; Peter Vock; Zsolt Szucs-Farkas Journal: Eur Radiol Date: 2011-05-31 Impact factor: 5.315
Authors: Luís S Guimarães; Joel G Fletcher; Lifeng Yu; James E Huprich; Jeff L Fidler; Armando Manduca; Juan Carlos Ramirez-Giraldo; David R Holmes; Cynthia H McCollough Journal: Acad Radiol Date: 2010-10 Impact factor: 3.173