Acceptable compression ratio of full-field digital mammography using JPEG 2000

ACVR and ECVDI consensus statement for teleradiology

Increased demand for the interpretation of diagnostic images by board-certified radiologists and profound advancements in technology have led to extremely rapid growth in the field of veterinary teleradiology over the past decade. The aim of this consensus statement is to provide a guideline for best practices for quality and safety in veterinary teleradiology. The statement addresses appropriate image acquisition and transmission, the creation of teleradiology submissions, quality control in teleradiology, and appropriate documentation of imaging reports, as deficiencies in any of these areas may directly affect the standard of patient care. The consensus statement may be used as a guide for radiologists, primary care veterinarians, technicians, and students for the use of teleradiology in practice.

Evaluation of lossy data compression in primary interpretation for full-field digital mammography

OBJECTIVE. For full-field digital mammography (FFDM), federal regulations prohibit lossy data compression for primary reading and archiving, unlike all other medical images, where reading physicians can apply their professional judgment in implementing lossy compression. Faster image transfer, lower costs, and greater access to expert mammographers would result from development of a safe standard for primary interpretation and archive of lossy-compressed FFDM images. This investigation explores whether JPEG 2000 80:1 lossy data compression affects clinical accuracy in digital mammography. MATERIALS AND METHODS. Randomized FFDM cases (n = 194) were interpreted by six experienced mammographers with and without JPEG 2000 80:1 lossy compression applied. A cancer-enriched population was used, with just less than half of the cases (42%) containing subtle (< 1 cm) biopsy-proven cancerous lesions, and the remaining cases were negative as proven by 2-year follow-up. Data were analyzed using the jackknife alternative free-response ROC (JAFROC) method. RESULTS. The differences in reader performance between lossy-compressed and non-lossy-compressed images using lesion localization (0.660 vs 0.671), true-positive fraction (0.879 vs 0.879), and false-positive fraction (0.283 vs 0.271) were not statistically significant. There was no difference in the JAFROC figure of merit between lossy-compressed and non-lossy-compressed images, with a mean difference of -0.01 (95% CI, -0.03 to 0.01; F1,5 = 2.30; p = 0.189). CONCLUSION. These results suggest that primary interpretation of JPEG 2000 80:1 lossy-compressed FFDM images may be viable without degradation of clinical quality. Benefits would include lower storage costs, faster telemammography, and enhanced access to expert mammographers.

Quantitative visually lossless compression ratio determination of JPEG2000 in digitized mammograms

The current study presents a quantitative approach towards visually lossless compression ratio (CR) threshold determination of JPEG2000 in digitized mammograms. This is achieved by identifying quantitative image quality metrics that reflect radiologists' visual perception in distinguishing between original and wavelet-compressed mammographic regions of interest containing microcalcification clusters (MCs) and normal parenchyma, originating from 68 images from the Digital Database for Screening Mammography. Specifically, image quality of wavelet-compressed mammograms (CRs, 10:1, 25:1, 40:1, 70:1, 100:1) is evaluated quantitatively by means of eight image quality metrics of different computational principles and qualitatively by three radiologists employing a five-point rating scale. The accuracy of the objective metrics is investigated in terms of (1) their correlation (r) with qualitative assessment and (2) ROC analysis (A z index), employing pooled radiologists' rating scores as ground truth. The quantitative metrics mean square error, mean absolute error, peak signal-to-noise ratio, and structural similarity demonstrated strong correlation with pooled radiologists' ratings (r, 0.825, 0.823, -0.825, and -0.826, respectively) and the highest area under ROC curve (A z , 0.922, 0.920, 0.922, and 0.922, respectively). For each quantitative metric, the highest accuracy values of corresponding ROC curves were used to define metric cut-off values. The metrics cut-off values were subsequently used to suggest a visually lossless CR threshold, estimated to be between 25:1 and 40:1 for the dataset analyzed. Results indicate the potential of the quantitative metrics approach in predicting visually lossless CRs in case of MCs in mammography.

Determining optimal medical image compression: psychometric and image distortion analysis

Background

Storage issues and bandwidth over networks have led to a need to optimally compress medical imaging files while leaving clinical image quality uncompromised.

Methods

To determine the range of clinically acceptable medical image compression across multiple modalities (CT, MR, and XR), we performed psychometric analysis of image distortion thresholds using physician readers and also performed subtraction analysis of medical image distortion by varying degrees of compression.

Results

When physician readers were asked to determine the threshold of compression beyond which images were clinically compromised, the mean image distortion threshold was a JPEG Q value of 23.1 ± 7.0. In Receiver-Operator Characteristics (ROC) plot analysis, compressed images could not be reliably distinguished from original images at any compression level between Q = 50 and Q = 95. Below this range, some readers were able to discriminate the compressed and original images, but high sensitivity and specificity for this discrimination was only encountered at the lowest JPEG Q value tested (Q = 5). Analysis of directly measured magnitude of image distortion from subtracted image pairs showed that the relationship between JPEG Q value and degree of image distortion underwent an upward inflection in the region of the two thresholds determined psychometrically (approximately Q = 25 to Q = 50), with 75 % of the image distortion occurring between Q = 50 and Q = 1.

Conclusion

It is possible to apply lossy JPEG compression to medical images without compromise of clinical image quality. Modest degrees of compression, with a JPEG Q value of 50 or higher (corresponding approximately to a compression ratio of 15:1 or less), can be applied to medical images while leaving the images indistinguishable from the original.