Wavelet based volumetric medical image compression

• Published in: Signal processing. Image communication 2015-02, Vol.31, p.112-133
• Main Authors: Bruylants, Tim, Munteanu, Adrian, Schelkens, Peter
• Format: Article
• Language: English
• Subjects: Codec; Directional wavelets; Guidelines; H.265/MPEG-H HEVC; Image compression; JP3D; JPEG 2000; JPEG encoders-decoders; JPEG-LS; Medical imaging; Performance enhancement; Subjective evaluation; Wavelet transforms
• ISSN: 0923-5965; 1879-2677
• DOI: 10.1016/j.image.2014.12.007

The amount of image data generated each day in health care is ever increasing, especially in combination with the improved scanning resolutions and the importance of volumetric image data sets. Handling these images raises the requirement for efficient compression, archival and transmission techniques. Currently, JPEG 2000׳s core coding system, defined in Part 1, is the default choice for medical images as it is the DICOM-supported compression technique offering the best available performance for this type of data. Yet, JPEG 2000 provides many options that allow for further improving compression performance for which DICOM offers no guidelines. Moreover, over the last years, various studies seem to indicate that performance improvements in wavelet-based image coding are possible when employing directional transforms. In this paper, we thoroughly investigate techniques allowing for improving the performance of JPEG 2000 for volumetric medical image compression. For this purpose, we make use of a newly developed generic codec framework that supports JPEG 2000 with its volumetric extension (JP3D), various directional wavelet transforms as well as a generic intra-band prediction mode. A thorough objective investigation of the performance-complexity trade-offs offered by these techniques on medical data is carried out. Moreover, we provide a comparison of the presented techniques to H.265/MPEG-H HEVC, which is currently the most state-of-the-art video codec available. Additionally, we present results of a first time study on the subjective visual performance when using the aforementioned techniques. This enables us to provide a set of guidelines and settings on how to optimally compress medical volumetric images at an acceptable complexity level. •We investigated how to optimally compress volumetric medical images with JP3D.•We extend JP3D with directional wavelets and intra-band prediction.•Volumetric wavelets and entropy-coding improve the compression performance.•Compression gains for medical images with directional wavelets are often minimal.•We recommend further adoption of JP3D for volumetric medical image compression.