Halpern E J, Premkumar A, Mullen D J, Ng C C, Levy H M, Newhouse J H, Amis E S, Sanders L M, Mun I K
Department of Radiology, Columbia Presbyterian Medical Center, New York, New York 10032.
Invest Radiol. 1990 Jun;25(6):703-7. doi: 10.1097/00004424-199006000-00015.
A quadtree-based data compression algorithm can provide different levels of compression within and outside of regions of interest (ROIs). The current study shows whether ROI compression can provide greater compression or diagnostic accuracy than uniform quadtree compression. In 75 single CT images from 75 consecutive abdominal examinations, 43 abnormalities were identified and surrounded by ROIs. Three radiologists interpreted the images following (1) 50:1 compression of the entire image; (2) ROI compression at five decreasing compression ratios (with 50:1 compression outside the ROI); and (3) reversible (lossless) compression of the entire image. Reversible compression (compression ratio 3:1) yielded a sensitivity of 96%. ROI compression of 15:1 was achieved with no loss of sensitivity; ROI compression of 28:1 yielded a sensitivity of 91% (not significantly different). At any given compression ratio, diagnostic sensitivity was greater with ROI compression than with uniform quadtree compression. For purposes of image archiving, quadtree-based ROI compression is superior to uniform compression of CT images.
基于四叉树的数据压缩算法可以在感兴趣区域（ROI）内外提供不同程度的压缩。当前研究表明，与均匀四叉树压缩相比，ROI压缩是否能提供更高的压缩率或诊断准确性。在75例连续腹部检查的75幅CT单图像中，识别出43处异常并将其用ROI包围。三位放射科医生对图像进行解读，分别是：（1）对整个图像进行50:1的压缩；（2）以五种递减的压缩率进行ROI压缩（ROI外为50:1压缩）；（3）对整个图像进行可逆（无损）压缩。可逆压缩（压缩率3:1）的敏感度为96%。实现了15:1的ROI压缩且不损失敏感度；28:1的ROI压缩敏感度为91%（无显著差异）。在任何给定的压缩率下，ROI压缩的诊断敏感度均高于均匀四叉树压缩。对于图像存档而言，基于四叉树的ROI压缩优于CT图像的均匀压缩。
