Effect of CT digital image compression on detection of coronary artery calcification

Emergence of teleradiology, PACS, and other radiology IT solutions in Acta Radiologica

For this historical review, we searched a database containing all the articles published in Acta Radiologica during its 100-year history to find those on the use of information technology (IT) in radiology. After reading the full texts, we selected the presented articles according to major radiology IT domains such as teleradiology, picture archiving and communication systems, image processing, image analysis, and computer-aided diagnostics in order to describe the development as it appeared in the journal. Publications generally follow IT megatrends, but because the contents of Acta Radiologica are mainly clinically oriented, some technology achievements appear later than they do in journals discussing mainly imaging informatics topics.

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.

Irreversible JPEG 2000 compression of abdominal CT for primary interpretation: assessment of visually lossless threshold

To estimate the visually lossless threshold for Joint Photographic Experts Group (JPEG) 2000 compression of contrast-enhanced abdominal computed tomography (CT) images, 100 images were compressed to four different levels: a reversible (as negative control) and irreversible 5:1, 10:1, and 15:1. By alternately displaying the original and the compressed image on the same monitor, six radiologists independently determined if the compressed image was distinguishable from the original image. For each reader, we compared the proportion of the compressed images being rated distinguishable from the original images between the reversible compression and each of the three irreversible compressions using the exact test for paired proportions. For each reader, the proportion was not significantly different between the reversible (0-1%, 0/100 to 1/100) and irreversible 5:1 compression (0-3%). However, the proportion significantly increased with the irreversible 10:1 (95-99%) and 15:1 compressions (100%) versus reversible compression in all readers (P < 0.001); 100 and 95% of the 5:1 compressed images were rated indistinguishable from the original images by at least five of the six readers and all readers, respectively. Irreversibly 5:1 compressed abdominal CT images are visually lossless and, therefore, potentially acceptable for primary interpretation.

Acute cerebral infarction: effect of JPEG compression on detection at CT

PURPOSE

To evaluate the effect of Joint Photographic Experts Group (JPEG) compression ratios of 10:1 and 20:1 on detection of acute cerebral infarction at computed tomography (CT).

MATERIALS AND METHODS

CT images obtained in 25 patients with acute cerebral infarction and 25 patients with no lesions were compressed by means of a JPEG algorithm at ratios of 10:1 and 20:1. Normal and abnormal sections (on original and compressed images) were reviewed by using a color soft-copy computed monochrome cathode ray tube monitor. Five observers rated the presence or absence of a lesion with a 50-point scale (0, definitely absent; 25, equivocal; and 50, definitely present). Diagnostic accuracy was evaluated with receiver operating characteristic (ROC) curve analysis. Significant difference was defined as a P value less than.05 for the area tested with a two-tailed paired Student t test.

RESULTS

At ROC analysis, no statistically significant difference was detected for all cases considered together (Az [area under the ROC curve] = 0.887 +/- 0.038 [mean +/- SD] on noncompressed images, Az = 0.897 +/- 0.038 on 10:1 compressed images, and Az = 0.842 +/- 0.073 on 20:1 compressed images; P >.05).

CONCLUSION

JPEG compression at ratios of 10:1 and 20:1 was tolerated in the detection of acute cerebral infarction at CT.

Wavelet compression on detection of brain lesions with magnetic resonance imaging

The purpose of this report is to assess clinically acceptable compression ratios on the detection of brain lesions at magnetic resonance imaging (MRI). Four consecutive T2-weighted and the corresponding T1-weighted images obtained in 20 patients were studied for 109 anatomic sites including 50 with lesions and 59 without lesions. The images were obtained on a 1.5-T MR unit with a pixel size of 0.9 to 1.2 x 0.47 mm and a section thickness of 5 mm. The image data were compressed by wavelet-based algorithm at ratios of 20:1, 40:1, and 60:1. Three radiologists reviewed these images on an interactive workstation and rated the presence or absence of a lesion with a 50 point scale for each anatomic site. The authors also evaluated the influence of pixel size on the quality of image compression. At receiver operating characteristic (ROC) analysis, no statistically significant difference was detected at a compression ratio of 20:1. A significant difference was observed with 40:1 compressed images for one reader (P = .023), and with 60:1 for all readers (P = .001 to .012). A root mean squared error (RMSE) was higher in 0.94- x 0.94-mm pixel size images than in 0.94- x 0.47-mm pixel size images at any compression ratio, indicating compression tolerance is lower for the larger pixel size images. The RMSE, subjective image quality, and error images of 10:1 compressed 0.94- x 0.94-mm pixel size images were comparable with those of 20:1 compressed 0.94- x 0.47-mm pixel size images. Wavelet compression can be acceptable clinically at ratios as high as 20:1 for brain MR images when a pixel size at image acquisition is around 1.0 x 0.5 mm, and as high as 10:1 for those with a pixel size around 1.0 x 1.0 mm.