With the increasing utilization of medical imaging in clinical practice and the growing dimensions of data volumes generated by various medical imaging modalities, the distribution, storage, and management of digital medical image data sets requires data compression. Over the past few decades, several image compression standards have been proposed by international standardization organizations. This paper discusses the current status of these image compression standards in medical imaging applications together with some of the legal and regulatory issues surrounding the use of compression in medical settings.

The lossless intra-prediction coding modality of the High Efficiency Video Coding standard provides high coding performance while allowing frame-by-frame basis access to the coded data. This is of interest in many professional applications, such as medical imaging, automotive vision, and digital preservation in libraries and archives. Various improvements to lossless intra-prediction coding have been proposed recently, most of them based on sample-wise prediction using differential pulse code modulation (DPCM). Other recent proposals aim at further reducing the energy of intra-predicted residual blocks. However, the energy reduction achieved is frequently minimal due to the difficulty of correctly predicting the sign and magnitude of residual values. In this paper, we pursue a novel approach to this energy-reduction problem using piecewise mapping (pwm) functions. In particular, we analyze the range of values in residual blocks and apply accordingly a pwm function to map specific residual values to unique lower values. We encode the appropriate parameters associated with the pwm functions at the encoder, so that the corresponding inverse pwm functions at the decoder can map values back to the same residual values. These residual values are then used to reconstruct the original signal. This mapping is, therefore, reversible and introduces no losses. We evaluate the pwm functions on 4 × 4 residual blocks computed after DPCM-based prediction for lossless coding of a variety of camera-captured and screen content sequences. Evaluation results show that the pwm functions can attain the maximum bitrate reductions of 5.54% and 28.33% for screen content material compared with DPCM-based and block-wise intra-prediction, respectively. Compared with intra-block copy, piecewise mapping can attain the maximum bit-rate reductions of 11.48% for a camera-captured material.

This paper presents a 3-D medical image coding method featuring two major improvements to previous work on 3-D region of interest (RoI) coding for telemedicine applications. Namely, 1) a data prioritization scheme that allows coding of multiple 3-D-RoIs; and 2) a joint/source channel coding scheme that allows prioritized transmission of multiple 3-D-RoIs over wireless channels. The method, which is based on the 3-D integer wavelet transform and embedded block coding with optimized truncation with 3-D context modeling, generates scalable and error-resilient bit streams with 3-D-RoI decoding capabilities. Coding of multiple 3-D-RoIs is attained by prioritizing the wavelet-transformed data according to a Gaussian mixed distribution, whereas error resiliency is attained by employing the error correction capabilities of rate-compatible punctured turbo codes. The robustness of the proposed method is evaluated for transmission of real 3-D medical images over Rayleigh-fading channels with a priori knowledge of the channel condition. Evaluation results show that the proposed coding method provides a superior performance compared to equal error protection and unequal error protection techniques.