Regional difference in compression artifacts in low-dose chest CT images: Effects of mathematical and perceptual factors

American Journal of Roentgenology

Volumn 191, Issue 2, 2008, Pages

  Kil, Joong Kim ^a,b   Kim, Bohyoung ^a   Lee, Kyoung Ho ^a   Tae, Jung Kim ^a   Mantiuk, Rafal ^c   Kang, Heung Sik ^a   Young, Hoon Kim ^a  

^a Seoul National University Bundang Hospital   (South Korea)

^b Seoul National University College of Medicine   (South Korea)

^c UNIVERSITY OF BRITISH COLUMBIA   (Canada)

Author keywords

Artifacts; CT; Data compression; Image quality metric; Low dose CT; Lung cancer screening; Visually lossless threshold

Indexed keywords

ADULT; AGED; ARTICLE; ARTIFACT; CLINICAL ARTICLE; COMPUTER ASSISTED TOMOGRAPHY; FEMALE; HUMAN; MALE; MATHEMATICAL ANALYSIS; MEDIASTINUM; PERCEPTION; PRIORITY JOURNAL; RADIOLOGIST; REPRODUCIBILITY; SIGNAL NOISE RATIO; STATISTICAL SIGNIFICANCE; THORAX WALL; WILCOXON SIGNED RANKS TEST;

ADULT; AGED; ALGORITHMS; ARTIFACTS; DATA COMPRESSION; FEMALE; HUMANS; MALE; MEDIASTINUM; MIDDLE AGED; RADIATION DOSAGE; RADIOGRAPHY, THORACIC; REPRODUCIBILITY OF RESULTS; SOLITARY PULMONARY NODULE; STATISTICS, NONPARAMETRIC; THORACIC WALL; TOMOGRAPHY, X-RAY COMPUTED;

EID: 49149120343     PISSN: 0361803X     EISSN: None     Source Type: Journal    
DOI: 10.2214/AJR.07.3462     Document Type: Article

References (25)

1. Ko JP, Rusinek H, Naidich DP, et al. Wavelet compression of low-dose chest CT data: effect on lung nodule detection. Radiology 2003; 228:70-75
2. Lee KH, Lee HJ, Kim JH, et al. Managing the CT data explosion: initial experiences of archiving volumetric datasets in a mini-PACS. J Digit Imaging 2005; 18:188-195
3. Erickson BJ, Manduca A, Palisson P, et al. Wavelet compression of medical images. Radiology 1998; 206:599-607
4. Ringl H, Schernthaner RE, Bankier AA, et al. JPEG2000 compression of thin-section CT images of the lung: effect of compression ratio on image quality. Radiology 2006; 240:869-877
5. Li F, Sone S, Takashima S, et al. Effects of JPEG and wavelet compression of spiral low-dose CT images on detection of small lung cancers. Acta Radiol 2001; 42:156-160
6. Kim TJ, Lee KH, Kim B, et al. Regional variance of visually lossless threshold in compressed chest CT images: lung versus mediastinum and chest wall. Eur J Radiol 2008 Jan 12 [Epub ahead of print; doi:10.1016/j.ejrad.2007. 11.035]
7. Woo HS, Kim KJ, Kim TJ, et al. JPEG 2000 compression of abdominal CT: difference in tolerance between thin- and thick-section images. AJR 2007; 189:535-541
8. Slone RM, Muka E, Pilgram TK. Irreversible JPEG compression of digital chest radiographs for primary interpretation: assessment of visually lossless threshold. Radiology 2003; 228:425-429
9. Eckert MP, Bradley AP. Perceptual quality metrics applied to still image compression. Signal Processing 1998; 70:177-200
10. Mantiuk R, Daly S, Myszkowski K, Seidel H-P. Predicting visible differences in high dynamic range images: model and its calibration. Proc Human Vision and Electronic Imaging X, IS&T/SPIE's 17th Annual Symposium on Electronic Imaging. Bellingham, WA: SPIE, 2005:204-214
11. Mantiuk R. HDR visual difference predictor. sourceforge.net/projects/ hdrvdp. Accessed July 4, 2006
12. Kim KJ, Kim B, Choi SW, et al. Definition of compression ratio: difference between two commercial JPEG2000 program libraries. Telemed J E Health 2008 (in press)
13. [No authors listed]. Digital Imaging and Communications in Medicine (DICOM) part 14: Grayscale standard display function. Rosslyn, VA: National Electrical Manufacturers Association, 2006: NEMA standards publication no. PS 3.14-2006, Va
14. Quick RF Jr. A vector-magnitude model of contrast detection. Kybernetik 1974; 16:65-67
15. Fleiss JL, Nee CM, Landis JR. Large sample variance of kappa in the case of different sets of raters. Psychol Bull 1979; 86:974-977
16. Liddell FD. Simplified exact analysis of case-referent studies: matched pairs, dichotomous exposure. J Epidemiol Community Health 1983; 37: 82-84
17. Rabbani M, Joshi R. An overview of the JPEG2000 still image compression standard. Signal Process: Image Comm 2002; 17:3-48
18. Gonzalez RC, Woods RE. Image compression. In: Gonzalez RC, ed. Digital image processing, 2nd ed. Upper Saddle River, NJ: Prentice Hall, 2002: 417-419
19. Krupinski EA, Johnson J, Roehrig H, et al. Using a human visual system model to optimize softcopy mammography display. Acad Radiol 2003; 10:1030-1035
20. Kim B, Lee KH, Kim KJ, et al. Prediction of perceptible artifacts in JPEG2000 compressed abdomen CT images using a perceptual image quality metric. Acad Radiol 2008; 15:314-325
21. Siddiqui KM, Johnson JP, Reiner BI, Siegel EL. Discrete cosine transform JPEG compression vs. 2D JPEG2000 compression: JNDmetrix visual discrimination model image quality analysis. Proc SPIE 2005; 5748:202-207
22. Siddiqui KM, Siegel EL, Reiner BI, Johnson JP. Correlation of radiologists' image quality perception with quantitative assessment parameters: just-noticeable difference vs. peak signal-to-noise ratios. Proc SPIE 2005; 5748:58-64
23. Kim B, Lee KH, Kim KJ, et al. Prediction of perceptible artifacts in JPEG 2000-compressed chest CT images using mathematical and perceptual quality metrics. AJR 2008; 190:328-334
24. Slone RM, Foos DH, Whiting BR, et al. Assessment of visually lossless irreversible image compression: comparison of three methods by using an image-comparison workstation. Radiology 2000; 215:543-553
25. Lee KH, Kim YH, Kim BH, et al. Irreversible JPEG 2000 compression of abdominal CT for primary interpretation: assessment of visually lossless threshold. Eur Radiol 2007; 17:1529-1534