Wu Yung-Gi
Department of Computer Science and Information Engineering, Leader University, Tainan City, Taiwan, ROC.
IEEE Trans Inf Technol Biomed. 2002 Mar;6(1):86-94. doi: 10.1109/4233.992167.
Advanced medical imaging requires storage of large quantities of digitized clinical data. Due to the constrained bandwidth and storage capacity, however, a medical image must be compressed before transmission and storage. Among the existing compression schemes, transform coding is one of the most effective strategies. Image data in spatial domain will be transformed into spectral domain after the transformation to attain more compression gains. Based on the quantization strategy, coefficients of low amplitude in the transformed domain are discarded and significant coefficients are preserved to increase the compression ratio without inducing salient distortion. In this paper, we use an adaptive sampling algorithm by calculating the difference area between correct points and predicted points to decide the significant coefficients. Recording or transmitting the significant coefficients instead of the whole coefficients achieves the goal of compression. On the decoder side, a linear equation is employed to reconstruct the coefficients between two sequent significant coefficients. Simulations are carried out to different medical images, which include sonogram, angiogram, computed tomography, and X-ray images. Consequent images demonstrate the performance at compression ratios of 20-45 without perceptible alterations. In addition, two doctors are invited to verify that the decoded quality is acceptable for practical diagnosis. Therefore, our proposed method is found to preserve information fidelity while reducing the amount of data.
先进的医学成像需要存储大量数字化临床数据。然而，由于带宽和存储容量受限，医学图像在传输和存储之前必须进行压缩。在现有的压缩方案中，变换编码是最有效的策略之一。经过变换后，空间域中的图像数据将被转换到频域以获得更高的压缩率。基于量化策略，变换域中低幅度系数被舍弃，重要系数被保留，以在不引起明显失真的情况下提高压缩比。在本文中，我们通过计算正确点与预测点之间的差异区域来使用自适应采样算法，以确定重要系数。记录或传输重要系数而非全部系数实现了压缩目标。在解码器端，使用线性方程来重建两个连续重要系数之间的系数。对不同的医学图像进行了模拟，包括超声图、血管造影、计算机断层扫描和X射线图像。结果图像展示了在20 - 45的压缩率下且无明显变化的性能。此外，邀请了两位医生来验证解码质量对于实际诊断是可接受的。因此，我们提出的方法在减少数据量的同时保持了信息保真度。
