Effects of JPEG2000 data compression on an automated system for detecting clustered microcalcifications in digital mammograms

• Published in: IEEE journal of biomedical and health informatics 2006-04, Vol.10 (2), p.354-361
• Main Authors: Penedo, M., Lado, M.J., Tahoces, P.G., Souto, M., Vidal, J.J.
• Format: Article
• Language: English
• Subjects: Artificial Intelligence; Biomedical imaging; Breast Diseases - diagnostic imaging; Calcinosis - diagnostic imaging; Communication standards; Computer science; Computer-aided detection (CAD); Data compression; Data Compression - methods; Data Compression - standards; DICOM; digital mammography; Female; Guidelines as Topic; Hospitals; Humans; Image coding; image compression; JPEG2000; Mammography; Mammography - methods; PSNR; Radiographic Image Enhancement - methods; Radiographic Image Interpretation, Computer-Assisted - methods; Reproducibility of Results; Sensitivity and Specificity; Transform coding
• ISSN: 1089-7771; 2168-2194; 1558-0032; 2168-2208
• DOI: 10.1109/TITB.2005.864381

The functionalities of the JPEG2000 standard have led to its incorporation into digital imaging and communications in medicine (DICOM), which makes this compression method available for medical systems. In this study, we evaluated the compression of mammographic images with JPEG2000 (16:1, 20:1, 40:1, 60.4:1, 80:1, and 106:1) for applications with a computer-aided detection (CAD) system for clusters of microcalcifications. Jackknife free-response receiver operating characteristic (JAFROC) analysis indicated that differences in the detection of clusters of microcalcifications were not statistically significant for uncompressed versus 16:1 (T=-0.7780;p=0.4370),20:1(T=1.0361;p=0.3007), and 40:1 (T=1.6966;p=0.0904); and statistically significant for uncompressed versus 60.4:1 (T=5.8883;p