Task-Oriented Compression for Medical Images

Medical imaging techniques produces a lot of digital images. Conventionally, lossless compression methods are used to make store and transmission to be more effective. To achieve high compression ratio, lossy compression must be exploited. However, lossy compression will distorted the original images and so have to be applied carefully. A medical image composes of two categories of regions. The regions in the first category include important information for diagnosis. The compression with very good quality of reconstructed image is necessary to these regions since the cost due to error representation will be high. On the other hand, information in the other category of regions may be less important and so compression to these regions should achieve high ratio. Based on this idea, we proposed a task oriented compression algorithm for medical images in this paper. We integrate the lossless compression and lossy compression via wavelet transform. Lossless compression is applied to the regions of interest and lossy compression to other regions. The proposed algorithm performs well in both compression ratio and quality of reconstructed image.