Evaluation of diagnostic accuracy of CRT monitor display for personal computer in the detection of small lung nodules: with particular emphasis on comparison between JPEG and wavelet compression

PURPOSE: To compare observer performance on cathode-ray-tube(CRT) monitors for personal computers with that on conventional radiographs in the detection of small lung nodules. MATERIALS AND METHODS: Fifty-eight normal chest radiographs and 58 chest radiographs with a small lung nodule were selected. Ten radiologists examined the original conventional films on a viewbox and digitized (8 bit) uncompressed and compressed images of the same patient on a color CRT monitor with a matrix of 1,600 x 1,200, and rated the presence of lung nodules with a five-level scale of confidence. The methods of compression used in this study were the JPEG and wavelet methods, with compression ratios of 6:1 and 15:1. Results were analyzed by receiver operating characteristic methods. RESULTS: There was no significant difference between film and digitized uncompressed and compressed images obtained by the JPEG and wavelet methods with a compression ratio of 6:1. No statistically significant difference was detected between film and digitized image with wavelet compression at 15:1. However, detection was less accurate on digitized images with JPEG compression at 15:1. CONCLUSION: Digitized (8 bit) uncompressed and compressed images with a compression ratio of 6:1 are acceptable for the detection of small lung nodules. Digitized compressed images at a compression ratio of 15:1 are also acceptable when the wavelet method is used.     

A comparison of two compression algorithms and the detection of caries

OBJECTIVES: To assess the effect of two compression algorithms (JPEG and wavelet) on the detection of approximal caries. METHODS: Fifteen bitewing radiographs were generated using 100 posterior teeth mounted in blocks. The images were produced on conventional films (Ektaspeed Plus) and scanned at 300 d.p.i. Digital images were then compressed 9:1 with JPEG and wavelet methods. Nine observers detected the presence and depth of approximal caries recorded on a 5-point confidence scale and a 4-point depth scale from images viewed in random order. Histological examination provided the true depth of the lesions. Data were analysed by means of ANOVA. The null hypothesis was that there is no significant difference between the two compression algorithms and the original uncompressed images. RESULTS: JPEG performed significantly worse than the original and the wavelet algorithm (P<0.001) for the detection of dentinal lesions. However, no significant differences were found for the detection of sound surfaces, enamel lesions, and lesions up to the DEJ between JPEG-compressed images and each of the other two modalities. There was also no significant difference between the wavelet-compressed images and the original for all lesion depths. CONCLUSIONS: At a compression ratio of 9:1, there were no significant differences among the original images, JPEG and wavelet compressed images for the detection of enamel caries. JPEG-compressed images performed inferiorly to the original and wavelet-compressed images for the detection of dentinal lesions. Wavelet compression is a better choice than JPEG at the compression ratio investigated in this study.     

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

Purpose: To test the effect of digital compression of CT images on the detection of small linear or spotted high attenuation lesions such as coronary artery calcification (CAC).Material and Methods: Fifty cases with and 50 without CAC were randomly selected from a population that had undergone spiral CT of the thorax for screening lung cancer. CT image data were compressed using JPEG (Joint Photographic Experts Group) or wavelet algorithms at ratios of 10:1, 20:1 or 40:1. Five radiologists reviewed the uncompressed and compressed images on a cathode-ray-tube. Observer performance was evaluated with receiver operating characteristic analysis.Results: CT images compressed at a ratio as high as 20:1 were acceptable for primary diagnosis of CAC. There was no significant difference in the detection accuracy for CAC between JPEG and wavelet algorithms at the compression ratios up to 20:1. CT images were more vulnerable to image blurring on the wavelet compression at relatively lower ratios, and "blocking" artifacts occurred on the JPEG compression at relatively higher ratios.Conclusion: JPEG and wavelet algorithms allow compression of CT images without compromising their diagnostic value at ratios up to 20:1 in detecting small linear or spotted high attenuation lesions such as CAC, and there was no difference between the two algorithms in diagnostic accuracy.     

Effects of JPEG and wavelet compression of spiral low-dose ct images on detection of small lung cancers

Purpose: To compare the effect of compression of spiral low-dose CT images by the Joint Photographic Experts Group (JPEG) and wavelet algorithms on detection of small lung cancers.Material and Methods: Low-dose spiral CT images of 104 individuals (52 with peripheral lung cancers smaller than 20 mm and 52 control subjects) were used. The original images were compressed using JPEG or wavelet algorithms at a ratio of 10:1 or 20:1. Five radiologists interpreted these images and evaluated the image quality on a high-resolution CRT monitor. Observer performance was studied by receiver operating characteristic (ROC) analysis.Results: There was no significant difference in the detection of cancers measuring 6 to 15 mm in uncompressed images and in those compressed by either of the algorithms, although the quality of images compressed at 20:1 with the wavelet algorithm was somewhat inferior. A lower diagnostic accuracy was noted using images compressed by the JPEG or wavelet algorithms at 20:1 in detecting lung cancers measuring 6 to 10 mm and cancers measuring from 6 to 15 mm with ground-glass opacity.Conclusion: Compression of low-dose CT images at a ratio of 10:1 using JPEG and wavelet algorithms does not compromise the detection rate of small lung cancers.     

Assessment of visually lossless irreversible image compression: comparison of three methods by using an image-comparison workstation

PURPOSE: To determine the degree of irreversible image compression detectable in conservative viewing conditions. MATERIALS AND METHODS: An image-comparison workstation, which alternately displayed two registered and magnified versions of an image, was used to study observer detection of image degradation introduced by irreversible compression. Five observers evaluated 20 16-bit posteroanterior digital chest radiographs compressed with Joint Photographic Experts Group (JPEG) or wavelet-based trellis-coded quantization (WTCQ) algorithms at compression ratios of 8:1-128:1 and x2 magnification by using (a) traditional two-alternative forced choice; (b) original-revealed two-alternative forced choice, in which the noncompressed image is identified to the observer; and (c) a resolution-metric method of matching test images to degraded reference images. RESULTS: The visually lossless threshold was between 8:1 and 16:1 for four observers. JPEG compression resulted in performance as good as that with WTCQ compression at these ratios. The original-revealed forced-choice method was faster and as sensitive as the two-alternative forced-choice method. The resolution-metric results were robust and provided information on performance above visually lossless levels. CONCLUSION: The image-comparison workstation is a versatile tool for comparative assessment of image quality. At x2 magnification, images compressed with either JPEG or WTCQ algorithms were indistinguishable from unaltered original images for most observers at compression ratios between 8:1 and 16:1, indicating that 10:1 compression is acceptable for primary image interpretation.     

Interaction between noise and file compression and its effect on the recognition of caries in digital imaging

OBJECTIVES: To determine the interaction between image noise and file compression, with special emphasis on the accuracy of caries diagnosis. METHODS: Fifty-nine bitewing radiographs of patients were taken simultaneously with Ektaspeed Plus (Eastman-Kodak, Rochester, NY, USA) film without lead foil and the Digora storage phosphor system (Soredex, Helsinki, Finland). Three different levels of Gaussian noise were added to the original digital images which were then compressed with JPEG 53. Seven observers evaluated the presence and depth of caries lesions on selected approximal surfaces on a 5-point scale. The results of JPEG 27 compression from a previous study were also included. ROC analysis was used together with multivariate analysis of variance (MANOVA). RESULTS: JPEG 27 and 53 reduced the file size down to 7% and 4.6% of the original respectively. ROC curve analysis showed no significant difference between image conditions (original, JPEG 27, and JPEG 53) at the same noise level. JPEG 27 and 53 had larger Az scores than their original counterparts at the same noise level. However, MANOVA showed that for depth estimation of enamel lesions JPEG 53 resulted in a higher observer error. CONCLUSIONS: Both JPEG 53 and 27 could reduce some of the adverse effect of noise from the image by removing high spatial frequencies. JPEG 53, resulting in a compression ratio of 1:21, does not compromise the diagnostic performance in general. JPEG 53 compression may however affect the ability to detect enamel lesions.     

Evaluation of JPEG and wavelet compression of body CT images for direct digital teleradiologic transmission

PURPOSE: To determine acceptable levels of JPEG (Joint Photographic Experts Group) and wavelet compression for teleradiologic transmission of body computed tomographic (CT) images. MATERIALS AND METHODS: A digital test pattern (Society of Motion Picture and Television Engineers, 512 x 512 matrix) was transmitted after JPEG or wavelet compression by using point-to-point and Web-based teleradiology, respectively. Lossless, 10:1 lossy, and 20:1 lossy ratios were tested. Images were evaluated for high- and low-contrast resolution, sensitivity to small signal differences, and misregistration artifacts. Three independent observers who were blinded to the compression scheme evaluated these image quality measures in 20 clinical cases with similar levels of compression. RESULTS: High-contrast resolution was not diminished with any tested level of JPEG or wavelet compression. With JPEG compression, low-contrast resolution was not lost with 10:1 lossy compression but was lost at 3% modulation with 20:1 lossy compression. With wavelet compression, there was loss of 1% modulation with 10:1 lossy compression and loss of 5% modulation with 20:1 lossy compression. Sensitivity to small signal differences (5% and 95% of the maximal signal) diminished only with 20:1 lossy wavelet compression. With 10:1 lossy compression, misregistration artifacts were mild and were equivalent with JPEG and wavelet compression. Qualitative clinical findings supported these findings. CONCLUSION: Lossy 10:1 compression is suitable for on-call electronic transmission of body CT images as long as original images are subsequently reviewed.     

The impact of image compression on diagnostic quality of digital images for detection of chemically-induced periapical lesions

OBJECTIVES: To test the hypothesis that there is no significant difference in the detectability of chemically-induced periapical lesions between a non-compressed image and one subjected to a Joint Photographic Experts Group (JPEG) lossy compression technique at a ratio of 23:1 or less. METHOD: Chemically-induced periapical lesions were created by placing a solution of 70% perchloric acid at the apex of extracted teeth in 13 human jaw cadaver specimens. Acid was applied in seven incremental time periods from 0-32 h. Extracted teeth were replaced in the socket and images were made using the Schick CDR digital sensor. Using a JPEG lossy compression algorithm, five compression ratios of 2:1, 14:1, 23:1, 28:1 and 47:1 were applied to the images. Images were viewed three times by three observers who ranked the presence or absence of a lesion at three sites, the mesial area, distal area and apex of the tooth, on a 5-point confidence scale. Intraobserver and interobserver agreement and agreement between the compressed and the original images were assessed with intraclass correlation coefficients (ICCs). RESULTS: Overall ICCs for measuring intraobserver agreement using all images were 0.77, 0.84, and 0.50 for the three observers, respectively. The overall ICC for assessing agreement between observers was 0.57. There was no significant difference (P>0.05) between compressed and original images for any site at compression ratios of 2:1, 23:1 and 28:1. There were significant differences for a compression ratio of 47:1. CONCLUSION: JPEG compression does not impact detectability of artificial periapical lesions at low and moderate compression ratios up to and including 28:1.     

Wavelet compression of low-dose chest CT data: effect on lung nodule detection

PURPOSE: To assess the effect of using a lossy Joint Photographic Experts Group standard for wavelet image compression, JPEG2000, on pulmonary nodule detection at low-dose computed tomography (CT). MATERIALS AND METHODS: One hundred sets of lung CT data ("cases") were compressed to 30:1, 20:1, and 10:1 levels by using a wavelet-based JPEG2000 method, resulting in 400 test cases. Each case consisted of nine 1.25-mm sections that had been obtained with 20-40 mAs. Four thoracic radiologists independently interpreted the test case images. Performance was measured by using area under the receiver operating characteristic (ROC) curve (Az) and conventional sensitivity and specificity analyses. RESULTS: There were 51 cases with and 49 without lung nodules. Az values were 0.984, 0.988, 0.972, 0.921, respectively, for original and 10:1, 20:1, and 30:1 compressed images. Az values decreased significantly at 30:1 (P =.014) but not at 10:1 compression, with a trend toward significant decrease at 20:1 (P =.051). Specificity values were unaffected by compression (>98.0% at all compression levels). Sensitivity values were 86.3% (176 of 204 test cases with nodules), 77.9% (159 of 204 cases), 76.5% (156 of 204 cases), and 70.1% (143 of 204 cases), respectively, for original and 10:1, 20:1, and 30:1 compressed images. Results of logistic regression model analysis confirmed the significant effects of compression rate and nodule attenuation, size, and location on sensitivity (P <.05). CONCLUSION: While no reduction in nodule detection at 10:1 compression levels was demonstrated by using ROC analysis, a significant decrease in sensitivity was identified. Further investigation is needed before widespread use of image compression technology in low-dose chest CT can be recommended.     

Irreversible JPEG compression of digital chest radiographs for primary interpretation: assessment of visually lossless threshold

PURPOSE: To determine if digital chest images could be compressed in a primary interpretation context without perceived loss of fidelity (below the visually lossless threshold) at transilluminated film or cathode ray tube (CRT) display. MATERIALS AND METHODS: One hundred forty-four posteroanterior radiographs were obtained with a digital chest radiography system. At both film and CRT display, an identified original image was presented side by side with a replicate, which was either an unaltered image or an image that had been Joint Photographic Experts Group (JPEG) compressed to 10:1, 20:1, or 50:1 and reconstructed. Each of the 10 readers indicated whether the replicate was "indistinguishable from the original" or "degraded" at clinical reading distance and at close inspection. The readers' ability to detect compressed images was examined for patterns; 95% CIs were used for statistical testing. RESULTS: With transilluminated film at clinical reading distance, readers were as likely to rate originals (48 [20%] of 240 readings) as degraded as they were to rate 20:1 replicates (106 [22%] of 480 readings) as degraded, but they frequently identified 50:1 replicates (283 [59%] of 480 readings) as degraded. At close inspection, 20:1 replicates (163 [34%] of 480 readings) were often identified as degraded, but 10:1 replicates (19 [8%] of 240 readings) were not identified as degraded more often than originals (17 [7%] of 240 readings). With CRT display, the results were nearly identical. CONCLUSION: At reading distance for primary interpretation, full-size digital chest radiographs that have been JPEG compressed to 10:1 or 20:1 and reconstructed are visually lossless at film or CRT display. Images compressed to 10:1 remain visually lossless at close inspection.     

Data compression: effect on diagnostic accuracy in digital chest radiography

High-resolution digital images make up very large data sets that are relatively slow to transmit and expensive to store. Data compression techniques are being developed to address this problem, but significant image deterioration can occur at high compression ratios. In this study, the authors evaluated a form of adaptive block cosine transform coding, a new compression technique that allows considerable compression of digital radiographs with minimal degradation of image quality. To determine the effect of data compression on diagnostic accuracy, observer tests were performed with 60 digitized chest radiographs (2,048 x 2,048 matrix, 1,024 shades of gray) containing subtle examples of pneumothorax, interstitial infiltrate, nodules, and bone lesions. Radiographs with no compression, with 25:1 compression, and with 50:1 compression ratios were presented in randomized order to 12 radiologists. The results suggest that, with this compression scheme, compression ratios as high as 25:1 may be acceptable for primary diagnosis in chest radiology.     

JPEG2000 compression of thin-section CT images of the lung: effect of compression ratio on image quality

PURPOSE: To assess retrospectively the effect of the Joint Photographic Experts Group 2000 (JPEG2000) compression ratio on the quality of thin-section computed tomographic (CT) images. MATERIALS AND METHODS: In this institutional review board-approved investigation (protocol 238/2004), thin-section CT images were subjected to irreversible JPEG2000 compression by using five compression ratios (3:1, 5:1, 7:1, 9:1, and 11:1). Three radiologists independently evaluated 60 thin-section CT images, of various diseases, that were obtained with single-detector (weighted dose index, 14.4 mGy) and multidetector (weighted dose index, 9.8 mGy) CT. Toggling between the original and compressed images, readers had to identify the original image by using a forced-choice two-alternative model and to subjectively rank the quality of what they believed to be the compressed image. To assess the reader's ability to distinguish the compressed from the original image, a binomial test was used. Bonferroni correction was applied for all multiple tests. RESULTS: Images compressed with a ratio of 3:1 were not distinguishable from original images (P > .2 for all readers). With use of the 5:1 ratio, minor differences in appearance between the compressed and original images were seen by one of the three readers. With use of higher compression ratios (>/=7:1), all readers (P < .001) recognized the original image. The quality of more than 90% of the images compressed with a 7:1 or higher ratio was substantially degraded. Single-detector and multidetector CT results were not significantly different. CONCLUSION: The highest ratio that yielded visually lossless compression of thin-section CT images was 3:1. With the 5:1 ratio, there was minor image quality loss, while use of higher compression ratios (>/=7:1) caused substantial degradation of image quality and potential loss of diagnostic information.     

Swelling archives warrant closer look at compression

Image compression is broadly categorized as lossless or lossy. With lossless compression, a compressed image can be decompressed and displayed as an exact digital replica of the original. With lossy compression, redundant pixel data are discarded during the compression process so that the compressed image is only an approximation of the original, therefore it cannot be returned to an original state. Although both types of compression are commonly used within the medical imaging community, institutions are much more likely to depend upon lossless compression for diagnostic purposes, even though lossy images, saved as a fraction of the original file size, are often diagnostically equivalent. With more and more digital modalities coming online and image studies growing ever larger, institutions failing to take full advantage of lossy compression are missing an opportunity to slow the growth of their image archives and IT infrastructure costs. Today, most PACS vendors include some form of image compression technology within their product offerings. Of 13 vendors sampled during an informal survey in June 2003, eight employ JPEG 2000 compression, which was incorporated into the DICOM standard in 2001, while the remainder use wavelet compression, which is the underlying methodology used in JPEG 2000. JPEG 2000 is an industry standard that enables image sharing across platforms and product lines. It also provides a single mechanism for creating lossless and lossy images, and gives institutions the flexibility to apply unique rates of compression to individual images based on modality, patient history, image size or other factors. Although it can be used judificiously to great advantage, compression is most often applied in an "across the board" manner to all images. The incorporation of JPEG 2000 within the DICOM standard does little to guarantee its longevity, or the quality of every JPEG 2000 implementation. At some point in time, especially as the demand for more compact, higher-quality lossy images grows, institutions will begin experimenting with and employing more advanced compression methods.     

Impact of JPEG lossy image compression on quantitative digital subtraction radiography

OBJECTIVES: The aim of the study was to evaluate the impact of JPEG lossy image compression on the estimation of alveolar bone gain by quantitative digital subtraction radiography (DSR). METHODS: Nine dry domestic pig mandible posterior segments were radiographed three times ('Baseline', 'No change', and 'Gain') with standardized projection geometry. Bone gain was simulated by adding artificial bone chips (1, 4, and 15 mg). Images were either compressed before or after registration. No change areas in compressed and subtracted 'No change-Baseline' images and bone gain volumes in compressed and subtracted 'Gain-Baseline' images were calculated and compared to the corresponding measurements performed on original subtracted images. RESULTS: Measurements of no change areas ('No change-Baseline') were only slightly affected by compressions down to JPEG 50 (J50) applied either before or after registration. Simulated gain of alveolar bone ('Gain-Baseline') was underestimated when compression before registration was performed. The underestimation was bigger when small bone chips of 1 mg were measured and when higher compression rates were used. Bone chips of 4 and 15 mg were only slightly underestimated when using J90, J70, and J50 compressions before registration. CONCLUSIONS: Lossy JPEG compression does not affect the measurements of no change areas by DSR. Images undergoing subtraction should be registered before compression and if so, J90 compression with a compression ratio of 1:7 can be used to detect and measure 4 mg and larger bone gain.     

Comparative evaluation of JPEG and JPEG2000 compression in quantitative digital subtraction radiography

OBJECTIVES: The aim of this in vitro study was to compare the impact of JPEG and the novel JPEG2000 compression standard on quantitative digital subtraction radiography (DSR) and to determine the acceptable JPEG2000 compression ratios for DSR. METHODS: Nine dry pig mandible sections were radiographed three times ('Baseline', 'No change', and 'Gain') with standardized projection geometry. Bone gain was simulated by adding artificial bone chips (1, 4 and 15 mg). Images were registered, compressed by JPEG and JPEG2000 using compression ratios (CR) of 1 : 7, 1 : 16, 1 : 22, and 1 : 31, and then subtracted. Image distortion was assessed objectively by calculating average pixel error and peak signal to noise ratio. No change areas in compressed and subtracted 'No change-Baseline' images and bone gain volumes in compressed and subtracted 'Gain-Baseline' images were calculated for both compression standards and compared. RESULTS: JPEG introduced less distortion at low CRs, while JPEG2000 was superior at higher CRs. At CR of 1 : 7, no significant difference between JPEG and JPEG2000 was found. JPEG2000 yielded better results for no change measurements at higher CRs. Volumes of simulated bone gain were overestimated when JPEG and underestimated when JPEG2000 compression was used. CONCLUSIONS: At CR of 1 : 7 JPEG and JPEG2000 performed similarly, which indicates that CR of 1:7 in JPEG2000 can be used for DSR if images are registered before compression. At higher CRs, JPEG2000 is superior to JPEG but image distortions are too high for reliable quantitative DSR.     

Detection of small peripheral lung cancer by digital chest radiography. Performance of unprocessed versus unsharp mask-processed images.

PURPOSE: To clarify whether processed digital chest radiography can improve the detection rate for small peripheral lung cancer. MATERIAL AND METHODS: Five radiologists independently interpreted 54 digitized chest radiographs of 18 patients with small peripheral lung cancers measuring less than 20 mm, which were displayed following 3 types of digital processing: 1) an original version; 2) unsharp mask processing with a type 1 filter (very low-frequency-enhancing, mid-frequency-suppressing, and high-frequency-enhancing filter); and 3) unsharp mask processing with a type 2 filter (very low- and high-frequency-enhancing filter). A total of 1,620 pooled observations were evaluated by receiver operating characteristic (ROC) analysis. RESULTS: The mean area under the ROC curves was 0.68 for the type 1 filter, 0.68 for the type 2 filter, and 0.65 for the unprocessed (original) image. There were no statistically significant differences among these 3 kinds of image processing (p>0.05). In all types of images, the small lung cancer with an alveolar lining tumor growth was less visible than a solid tumor growth (p<0.01); the sensitivity increased with tumor size when the 3 groups of cancers, those measuring less than 10 mm, 11-15 mm, and 16-20 mm, were compared (p<0.01). CONCLUSION: Unsharp mask-image processing of digital chest radiography will not improve the detection rate of small peripheral lung cancer, probably due to a substantial drawback: the limited conspicuity of cancer lesions in the surrounding lung and superposition of structures.     

Applying computer-assisted detection schemes to digitized mammograms after JPEG data compression: an assessment

RATIONALE AND OBJECTIVES: The authors' purpose was to assess the effects of Joint Photographic Experts Group (JPEG) image data compression on the performance of computer-assisted detection (CAD) schemes for the detection of masses and microcalcification clusters on digitized mammograms. MATERIALS AND METHODS: This study included 952 mammograms that were digitized and compressed with a JPEG-compatible image-compression scheme. A CAD scheme, previously developed in the authors' laboratory and optimized for noncompressed images, was applied to reconstructed images after compression at five levels. The performance was compared with that obtained with the original noncompressed digitized images. RESULTS: For mass detection, there were no significant differences in performance between noncompressed and compressed images for true-positive regions (P = .25) or false-positive regions (P = .40). In all six modes the scheme identified 80% of masses with less than one false-positive region per image. For the detection of microcalcification clusters, there was significant performance degradation (P < .001) at all compression levels. Detection sensitivity was reduced by 4%-10% as compression ratios increased from 17:1 to 62:1. At the same time, the false-positive detection rate was increased by 91%-140%. CONCLUSION: The JPEG algorithm did not adversely affect the performance of the CAD scheme for detecting masses, but it did significantly affect the detection of microcalcification clusters.     

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. This study was supported by Seoul R&BD Program, Republic of Korea (project number, 10675).     

Comparison of microscopy and radiography as gold standards in radiographic caries diagnosis

OBJECTIVES: To compare the effect of the choice of gold standard on the diagnostic outcome of approximal caries detection in original and compressed digital radiographs. METHODS: 116 extracted teeth radiographed with a storage phosphor system constituted the original images. These images were compressed at 1:20 and 1:33 with the JPEG irreversible compression standard. Five radiologists scored the three sets of images for the presence of approximal caries on a five-rank confidence scale. The radiographic scores were validated by stereomicroscopy (the true gold standard). The individual ROC areas for the five observers were used to select the worst (obsworst) and the best (obsbest) performer: Their scores in the original images were used as the second and third 'gold standards' for the remaining observers. Mean ROC areas for the three observers with the three types of images were calculated using these two new 'gold standards'. Differences between the ROC areas when using microscopy, obsworst, and obsbest as the 'gold standard' were compared. RESULTS: The mean ROC areas in the original images were 0.66, 0.74 and 0.91 using the true gold standard and obsbest and obsworst as the 'gold standards' respectively. The difference between the true gold standard and obsworst was statistically significant (P < 0.001). The mean ROC areas using the true gold standard decreased with increasing compression whereas they were constant or increased using obsworst and obsbest as 'gold standards', respectively. CONCLUSIONS: Accuracy in approximal caries diagnosis was significantly higher when an observer was the 'gold standard' than when the true gold standard was obtained by microscopy. Paradoxically, the compressed, degraded images were more accurate than the originals when an observer was the 'gold standard' while they were less accurate with the true gold standard. Thus, results obtained using observers' scores from the radiographs which are being evaluated, as validation for the presence of caries may mislead the clinician.     

Fractal-feature distance analysis of radiographic image

RATIONALE AND OBJECTIVES: We have conducted a fractal analysis of low-dose digital chest phantom radiographs and evaluated the relationship between the fractal-feature distance and the tube current-exposure time product. MATERIALS AND METHODS: Chest phantom radiographs were obtained at various mAs values (0.5-4.0 mAs) and 140 kVp with a computed radiography system, and the reference images were acquired at 13 mAs. The lung field images were converted to binary images after processing them using the rolling-ball technique; a fractal analysis was conducted using the box-counting method for these binary images. The fractal-feature distances between the low-dose and reference images were calculated using the fractal dimension and the complexity. RESULTS: For all binary images of lung fields, the relationship between the length of the square boxes and the number of boxes needed to cover the positive pixels of the binary image was linear on a log-log scale (r > or = 0.99). For mAs > or = 3.0, the fractal-feature distances were almost constant, whereas for mAs < or = 2.5, they increased depending on the reduction in mAs values. CONCLUSION: We have shown that a binary image of the lung field obtained from a chest phantom radiograph can be analyzed by the box-counting method and that its fractal-feature distance grows as the radiation dose declines.