JPEG 2000 compression of abdominal CT: difference in tolerance between thin- and thick-section images.

OBJECTIVE The purpose of our study was to compare the tolerance of Joint Photographic Experts Group (JPEG) 2000 compression between thin- and thick-section abdominal CT images. MATERIALS AND METHODS One hundred 0.67-mm-thick and corresponding 5-mm-thick images were compressed to four different levels: reversible and irreversible 6:1, 10:1, and 15:1. Five radiologists determined if the compressed images were distinguishable from the originals. The percentage of distinguishable pairs and peak signal-to-noise ratio (PSNR) were compared between the thin and thick sections. The visually lossless threshold was estimated by comparing the percentages of the distinguishable pairs between each irreversible compression and the reversible compression. Paired Student's t tests and exact tests for paired proportions were used. RESULTS Thin sections had smaller PSNRs at each compression level (p < 0.001). According to the pooled responses, the percentages of distinguishable pairs for the thin and thick sections, respectively, were 0% (0/100) and 0% at reversible compression, 27% and 0% at 6:1 (p < 0.001), 100% and 80% at 10:1 (p < 0.001), and 100% and 100% at 15:1. Artifacts increased significantly (p < 0.001) at 6:1 or more for the thin sections and at 10:1 and 15:1 for the thick sections, indicating that the visually lossless thresholds were below 6:1 and between 6:1 and 10:1, respectively. CONCLUSION Thin-section abdominal CT images are less tolerant of compression, and a lower compression level should be used for the visually lossless threshold.

[1]  G. James Blaine,et al.  Factors affecting the selection of compression algorithms for projection radiography , 1997, Medical Imaging.

[2]  Henry Rusinek,et al.  Computed Tomography Diagnosis Utilizing Compressed Image Data: An ROC Analysis Using Acute Appendicitis as a Model , 2002, Journal of Digital Imaging.

[3]  Jeffrey Lubin,et al.  The use of psychophysical data and models in the analysis of display system performance , 1993 .

[4]  Bo Hyoung Kim,et al.  Irreversible JPEG 2000 compression of abdominal CT for primary interpretation: assessment of visually lossless threshold , 2006, European Radiology.

[5]  T Umeda,et al.  Evaluation of compressed lung CT image quality using quantitative analysis. , 2001, Radiation medicine.

[6]  A. Manduca,et al.  Wavelet compression of medical images. , 1998, Radiology.

[7]  Mathias Prokop,et al.  JPEG2000 compression of thin-section CT images of the lung: effect of compression ratio on image quality. , 2006, Radiology.

[8]  Kevin McEnery,et al.  Impact of multislice CT on PACS resources. , 2002, Journal of digital imaging.

[9]  Michael F McNitt-Gray,et al.  AAPM/RSNA Physics Tutorial for Residents: Topics in CT. Radiation dose in CT. , 2002, Radiographics : a review publication of the Radiological Society of North America, Inc.

[10]  M Mahesh,et al.  Dose and pitch relationship for a particular multislice CT scanner. , 2001, AJR. American journal of roentgenology.

[11]  R A Olshen,et al.  Thoracic CT images: effect of lossy image compression on diagnostic accuracy. , 1994, Radiology.

[12]  Michael W Freckleton,et al.  Informatics in radiology (infoRAD): introduction to the language of three-dimensional imaging with multidetector CT. , 2005, Radiographics : a review publication of the Radiological Society of North America, Inc.

[13]  G. Rubin,et al.  Data explosion: the challenge of multidetector-row CT. , 2000, European journal of radiology.

[14]  Seokyung Hahn,et al.  Computed Tomography Diagnosis of Acute Appendicitis: Advantages of Reviewing Thin-section Datasets using Sliding Slab Average Intensity Projection Technique , 2006, Investigative radiology.

[15]  Geoffrey D Rubin,et al.  3-D imaging with MDCT. , 2003, European journal of radiology.

[16]  Yoshimitsu Ohgiya,et al.  Acute cerebral infarction: effect of JPEG compression on detection at CT. , 2003, Radiology.

[17]  S Sone,et al.  Effect of CT digital image compression on detection of coronary artery calcification. , 2000, Acta radiologica.

[18]  Edward Muka,et al.  Irreversible JPEG compression of digital chest radiographs for primary interpretation: assessment of visually lossless threshold. , 2003, Radiology.

[19]  Helen Hong,et al.  Managing the CT Data Explosion: Initial Experiences of Archiving Volumetric Datasets in a Mini-PACS , 2005, Journal of Digital Imaging.

[20]  J. R. Landis,et al.  The measurement of observer agreement for categorical data. , 1977, Biometrics.

[21]  G S Gazelle,et al.  Focal hepatic lesions: effect of three-dimensional wavelet compression on detection at CT. , 1997, Radiology.

[22]  Andrew B. Watson,et al.  Digital images and human vision , 1993 .

[23]  Thomas K. Pilgram,et al.  Perceived fidelity of compressed and reconstructed radiological images: A preliminary exploration of compression, luminance, and viewing distance , 2009, Journal of Digital Imaging.

[24]  Henry Rusinek,et al.  Wavelet compression of low-dose chest CT data: effect on lung nodule detection. , 2003, Radiology.

[25]  Bradley J. Erickson,et al.  Image display for clinicians on medical record workstations , 1997, Journal of Digital Imaging.

[26]  F. Liddell Simplified exact analysis of case-referent studies: matched pairs; dichotomous exposure. , 1983, Journal of epidemiology and community health.

[27]  J. Fleiss,et al.  The Reliability of Dichotomous Judgments: Unequal Numbers of Judges per Subject , 1979 .

[28]  Armando Manduca,et al.  An analytical look at the effects of compression on medical images , 1997, Journal of Digital Imaging.

[29]  P R Mueller,et al.  CT colonography with teleradiology: effect of lossy wavelet compression on polyp detection--initial observations. , 2001, Radiology.

[30]  J D Hazle,et al.  Introduction to wavelet-based compression of medical images. , 1998, Radiographics : a review publication of the Radiological Society of North America, Inc.

[31]  Henry Rusinek,et al.  Effect of CT image compression on computer-assisted lung nodule volume measurement. , 2005, Radiology.

[32]  Michael W. Marcellin,et al.  Compression of multislice CT: 2D vs. 3D JPEG2000 and effects of slice thickness , 2005, SPIE Medical Imaging.

[33]  S Sone,et al.  Effects of JPEG and wavelet compression of spiral low-dose ct images on detection of small lung cancers. , 2001, Acta radiologica.