OBJECTIVE: To determine acceptable compression ratios for digital radiography, we evaluated the effect of data compression on the detection of subtle interstitial lung abnormalities using digitized chest radiographs. MATERIALS AND METHODS: Screen-film chest radiographs of 38 patients with subtle interstitial lung abnormalities and 40 patients with normal lung parenchyma were digitized (spatial resolution, 0.175 mm; 2000 x 2000 pixels; 10 bits per pixel) and compressed with the discrete cosine transform method at ratios of 10:1, 20:1, and 30:1. Five chest radiologists and five radiology residents examined the uncompressed and compressed digital images and rates the presence of interstitial lung abnormalities with a five-level scale of confidence. Results were analyzed by receiver operating characteristic methods. RESULTS: Overall, the interpretation of images with a compression ratio of 30:1 was significantly less accurate than that of uncompressed images (p < .05). For the five chest radiologists, interpretation of images with a compression ratio of 20:1 or 30:1 was significantly less accurate than that of uncompressed images (p < .05). However, for the five residents, no significant difference between interpretations of compressed and uncompressed images was noted (p > or = .05). CONCLUSION: These results suggest that a 10:1 data compression ratio does not influence the detection of subtle interstitial lung abnormalities. However, information that is lost with a 20:1 data compression ratio might be essential for interpretation by experienced chest radiologists.
OBJECTIVE: To determine acceptable compression ratios for digital radiography, we evaluated the effect of data compression on the detection of subtle interstitial lung abnormalities using digitized chest radiographs. MATERIALS AND METHODS: Screen-film chest radiographs of 38 patients with subtle interstitial lung abnormalities and 40 patients with normal lung parenchyma were digitized (spatial resolution, 0.175 mm; 2000 x 2000 pixels; 10 bits per pixel) and compressed with the discrete cosine transform method at ratios of 10:1, 20:1, and 30:1. Five chest radiologists and five radiology residents examined the uncompressed and compressed digital images and rates the presence of interstitial lung abnormalities with a five-level scale of confidence. Results were analyzed by receiver operating characteristic methods. RESULTS: Overall, the interpretation of images with a compression ratio of 30:1 was significantly less accurate than that of uncompressed images (p < .05). For the five chest radiologists, interpretation of images with a compression ratio of 20:1 or 30:1 was significantly less accurate than that of uncompressed images (p < .05). However, for the five residents, no significant difference between interpretations of compressed and uncompressed images was noted (p > or = .05). CONCLUSION: These results suggest that a 10:1 data compression ratio does not influence the detection of subtle interstitial lung abnormalities. However, information that is lost with a 20:1 data compression ratio might be essential for interpretation by experienced chest radiologists.
Authors: D P Beall; P D Shelton; T V Kinsey; M C Horton; B J Fortman; S Achenbach; V Smirnoff; D L Courneya; B Carpenter; J T Gironda Journal: J Digit Imaging Date: 2000-05 Impact factor: 4.056
Authors: K Egashira; H Nakata; H Watanabe; K Uchida; K Nakamura; Y Ishino; K Horino; R Yoshikawa Journal: J Digit Imaging Date: 1998-11 Impact factor: 4.056
Authors: Uta Zaspel; David W Denning; Arne J Lemke; Reginald Greene; Dirk Schürmann; Georg Maschmeyer; Markus Ruhnke; Raoul Herbrecht; Patricia Ribaud; Olivier Lortholary; Harmien Zonderland; Klaus F Rabe; Rainer Röttgen; Roland Bittner; Klaus Neumann; Joerg W Oestmann Journal: Eur Radiol Date: 2004-08-11 Impact factor: 5.315