Context modeling based lossless compression of radio-frequency data for software-based ultrasound beamforming

A new lossless compression method using context modeling for ultrasound radio-frequency (RF) data is presented. In the proposed compression method, the combination of context modeling and entropy coding is used for effectively lowering the data transfer rates for modern software-based medical ultrasound imaging systems. From the phantom and in vivo data experiments, the proposed lossless compression method provides the average compression ratio of 0.45 compared to the Burg and JPEG-LS methods (0.52 and 0.55, respectively). This result indicates that the proposed compression method is capable of transferring 64-channel 40-MHz ultrasound RF data with a 16-lane PCI-Express 2.0 bus for software beamforming in real time.