Image compression and chest radiograph interpretation: Image perception comparison between uncompressed chest radiographs and chest radiographs stored using 10∶1 JPEG compression

Beall, Douglas P.; Shelton, Phillip D.; Kinsey, Thomas V.; Horton, Maria C.; Fortman, Brian J.; Achenbach, Steffen; Smirnoff, Vadim; Courneya, Daniel L.; Carpenter, Bill; Gironda, John T.

doi:10.1007/bf03167620

Cited by 15 publications

(12 citation statements)

References 12 publications

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“…5,6 Although image quality is the primary consideration, a risk versus bene®t analysis should consider other factors as well when deciding whether to use irreversible compression in clinical practice. The following additional factors should be considered:…”

Section: Discussionmentioning

confidence: 99%

Evaluation of Irreversible JPEG Compression for A Clinical Ultrasound Practice

et al. 2002

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A prior ultrasound study indicated that images with low to moderate levels of JPEG and wavelet compression were acceptable for diagnostic purposes. The purpose of this study is to validate this prior ®nding using the Joint Photographic Experts Group (JPEG) baseline compression algorithm, at a compression ratio of approximately 10:1, on a suf®ciently large number of grayscale and color ultrasound images to attain a statistically signi®cant result. The practical goal of this study is to determine if it is feasible for radiologists to use irreversibly compressed images as an integral part of the day to day ultrasound practice (ie, perform primary diagnosis with, and store irreversibly compressed images in the ultrasound PACS archive). In this study, 5 Radiologists were asked to review 300 grayscale and color static ultrasound images selected from 4 major anatomic groups. Each image was compressed and decompressed using the JPEG baseline compression algorithm at a ®xed quality factor resulting in an average compression ratio of approximately 9:1. The images were presented in pairs (original and compressed) in a blinded fashion on a PACS workstation in the ultrasound reading areas, and radiologists were asked to pick which image they preferred in terms of diagnostic utility and their degree of certainty (on a scale from 1 to 4). Of the 1,499 total readings, 50.17% (95% con®dence intervals at 47.6%, and 52.7%) indicated a preference for the original image in the pair, and 49.83% (95% con®dence intervals at 47.3%, and 52.0%) indicated a preference for the compressed image. These ®ndings led the authors to conclude that static color and gray-scale ultrasound images compressed with JPEG at approximately 9:1 are statistically indistinguishable from the originals for primary diagnostic purposes. Based on the authors laboratory experience with compression and the results of this and other prior studies JPEG compression is now being applied to all ultrasound images in the authors radiology practice before reading. No image quality±related issues have been encountered after 12 months of operation (approximately 48,000 examinations).KEY WORDS: Compression, Joint Photographic Experts Group, ultrasound, medical images, PACS, teleradiology, archive W ith the rapidly dropping cost of digital storage and conservative use of standards-based irreversible (lossy) compression techniques, it is becoming practical to maintain large volumes of clinical images online, and distribute them eciently over networks.A prior ultrasound compression study was performed by our group to evaluate the eects of irreversible wavelet compression on ultrasound images and to determine how much compression can be applied, and still have the images be``acceptable for diagnostic purposes.'' 1 That study focused speci®cally on grayscale ultrasound images and considered a variety of factors including wavelet compression at several compression levels, different acquisition techniques (frame-grabbed v directly digitally acquired) and the eects of text that is`b ur...

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Section: Discussionmentioning

confidence: 99%

Evaluation of Irreversible JPEG Compression for A Clinical Ultrasound Practice

et al. 2002

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“…Several investigators have found that diagnostic information may be preserved on digitized chest radiographs at levels as high as 20 to 25:1 allowing diagnosis of interstitial ®brosis, pneumothorax, and detection of lung nodules. 1,5,18 Others have evaluated image compression in digital mammography 13,20 and coronary angiography. 3,17 To date, an optimal compression rate has neither been established nor are the criteria that might be used to determine such optimum de®ned.…”

Section: Discussionmentioning

confidence: 99%

Computed Tomography Diagnosis Utilizing Compressed Image Data: An ROC Analysis Using Acute Appendicitis as a Model

Megibow

Rusinek

Lisi

et al. 2002

Journal of Digital Imaging

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Using receiver-operating characteristic (ROC) methodology, the ability to diagnose acute appendicitis with computed tomography (CT) images displayed at varying levels of lossy compression was evaluated. Nine sequential images over the ileocecal region were obtained from 53 consecutive patients with right lower quadrant pain who were clinically suspected to have acute appendicitis. Thirty were proven surgically to have acute appendicitis, alternative diagnoses con®rmed in 23. The image sets were subjected to a lossy wavelet-based compression algorithm``Embedded Predictive Wavelet Image Coder'' (EPWIC). Compression levels were: none, 8:1, 16:1, and 24:1, resulting in 4 sets of images per patient. Image sets were randomized and evaluated separately by 4 body radiologists on a 1,024´768-pixel SVGA color PC monitor in 512´512 format. The readers were aware of the clinical suspicion of appendicitis but were unaware of the positive fraction of cases. Individual and combined reader ROC and v 2 analyses of sensitivity, speci®city, and accuracy were determined. For all readers, sensitivity decreases at 16:1 and 24:1 levels (P < 0.01, P < 0.001, respectively). Accuracy decreased at 24:1 levels (P < 0.01). Speci®city was unaected. By ROC analysis there was statistically signi®cantly decreased area under the curve at 24:1 levels (P < 0.02) as compared with uncompressed images. Finite levels of lossy wavelet compression may be applied to CT images without compromising diagnostic performance.

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“…Mori and Nakata 27 proposed a ratio of 25:1 with Az of 0.883 for chest image compression. Aberle et al 28 and Beall et al 11 conducted similar works to detect lung nodules in compressed chest images and reported ratios of 20:1 and 10:1 at Az of 0.882 and 0.926, respectively.…”

Section: Roc Analysismentioning

confidence: 96%

“…8 Many researchers applied this method to examine their image quality on different set of images with different number of reviewers and different types of diseases. 9,10,11 …”

Section: Subjective Evaluationmentioning

confidence: 99%

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Wavelet compression algorithm applied to abdominal ultrasound images

Lin

Lee²,

Pan³

et al. 2006

Radiographer

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We sought to investigate acceptable compression ratios of lossy wavelet compression on 640 × 480 × 8 abdominal ultrasound (US) images. We acquired 100 abdominal US images with normal and abnormal findings from the view station of a 932‐bed teaching hospital. The US images were then compressed at quality factors (QFs) of 3, 10, 30, and 50 followed outcomes of a pilot study. This was equal to the average compression ratios of 4.3:1, 8.5:1, 20:1 and 36.6:1, respectively. Four objective measurements were carried out to examine and compare the image degradation between original and compressed images. Receiver operating characteristic (ROC) analysis was also introduced for subjective assessment. Five experienced and qualified radiologists as reviewers blinded to corresponding pathological findings, analysed paired 400 randomly ordered images with two 17‐inch thin film transistor/liquid crystal display (TFT/LCD) monitors. At ROC analysis, the average area under curve (Az) for US abdominal image was 0.874 at the ratio of 36.6:1. The compressed image size was only 2.7% for US original at this ratio. The objective parameters showed the higher the mean squared error (MSE) or root mean squared error (RMSE) values, the poorer the image quality. The higher signal‐to‐noise ratio (SNR) or peak signal‐to‐noise ratio (PSNR) values indicated better image quality. The average RMSE, PSNR at 36.6:1 for US were 4.84 ± 0.14, 35.45 dB, respectively. This finding suggests that, on the basis of the patient sample, wavelet compression of abdominal US to a ratio of 36.6:1 did not adversely affect diagnostic performance or evaluation error for radiologists' interpretation so as to risk affecting diagnosis

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Image compression and chest radiograph interpretation: Image perception comparison between uncompressed chest radiographs and chest radiographs stored using 10∶1 JPEG compression

Cited by 15 publications

References 12 publications

Evaluation of Irreversible JPEG Compression for A Clinical Ultrasound Practice

Evaluation of Irreversible JPEG Compression for A Clinical Ultrasound Practice

Computed Tomography Diagnosis Utilizing Compressed Image Data: An ROC Analysis Using Acute Appendicitis as a Model

Wavelet compression algorithm applied to abdominal ultrasound images

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