Tyler Clemons and Jian Yin
Medical Data Compression, Medical Data Storage, Medical Image Processing
High Resolution Medical Images provide a useful visual and analytic tool to medical professionals. These images often require substantial disk space and thus may provide bottlenecks in I/O access and network transmission, and create a challenge for disk storage capacity. These prob- lems can be mitigated by using compression algorithms that not only reduce the storage requirements of the data files, but can do so quickly as to meet real time workloads. We present a lossless entropy based compression scheme that achieves both of these goals for medical image data. We demonstrate the effectiveness of our lossless algorithm using a medical image dataset and compare its performance with other lossless compression techniques. Our method provides competitive compression ratios without sacrificing real-time performance.
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