Progressive Coding and Transmission of Digital Diagnostic Pictures

In radiology, as a result of the increased utilization of digital imaging modalities, such as computed tomography (CT) and magnetic resonance imaging (MRI), over a third of the images produced in a typical radiology department are currently in digital form, and this percentage is steadily increasing. Image compression provides a means for the economical storage and efficient transmission of these diagnostic pictures. The level of coding distortion that can be accepted for clinical diagnosis purposes is not yet well-defined. In this paper we introduce some constraints on the design of existing transform codes in order to achieve progressive image transmission efficiently. The design constraints allow the image quality to be asymptotically improved such that the proper clinical diagnoses are always possible. The modified transform code outperforms simple spatial-domain codes by providing higher quality of the intermediately reconstructed images. The improvement is 10 dB for a compression factor of 256:1, and it is as high as 17.5 dB for a factor of 8:1. A novel progressive quantization scheme is developed for optimal progressive transmission of transformed diagnostic images. Combined with a discrete cosine transform, the new approach delivers intermediately reconstructed images of comparable quality twice as fast as the more usual zig-zag sampled approach. The quantization procedure is suitable for hardware implementation.