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Open Access Open Badges Research article

Determining optimal medical image compression: psychometric and image distortion analysis

Alexander C Flint

Author affiliations

Interconnect Medical, LLC, Menlo Park, CA, 94025, USA

Citation and License

BMC Medical Imaging 2012, 12:24  doi:10.1186/1471-2342-12-24

Published: 31 July 2012



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


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.


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.


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.

Medical image compression; JPEG; Lossy; Psychometrics; Image analysis