Bio-medical Engineering Department, Tel Aviv University, Tel Aviv, Israel.
Comput Biol Med. 2011 Jun;41(6):367-79. doi: 10.1016/j.compbiomed.2011.03.015. Epub 2011 May 20.
Computerized Tomography (CT) images are High Dynamic Range (HDR) images of the X-ray attenuation coefficients of the body's tissues. The inability to see abnormalities in tissues with marked differences in their X-ray attenuation coefficients, in a single CT window, poses a significant clinical problem in radiology. In order to provide proper contrast, which reveals all the required clinical details within each specifically imaged tissue, a single CT slice must be viewed by a radiologist four times: the first viewing focuses on the lung window; the second viewing focuses on the soft tissues window; the third viewing focuses on the liver window; and the fourth viewing focuses on the bone window. In order to enhance the ability to perform a complete diagnosis, while decreasing diagnostic time, we developed the BACCT (Biologically-based Algorithm for Companding CT images) method. Our algorithm compresses and expands (compands) the HDR CT image into a single, low dynamic range image. Before performing the companding procedure, unique processing is required which involves operations that enhance and stretch the image. The performance of our algorithm has been demonstrated on a large repertoire of CT body images. All the clinically required CT information is exposed in each CT slice in a single image. The algorithm compands the CT images in a fully automatic way. Collaborating radiologists have already tested the results of our algorithmic method, and reported that the images seem to provide all the necessary information. However, clinical tests for statistical reliability are still required.
计算机断层扫描（CT）图像是人体组织 X 射线衰减系数的高动态范围（HDR）图像。在单一 CT 窗口中，由于组织的 X 射线衰减系数存在明显差异，无法看到异常情况，这在放射学中是一个重大的临床问题。为了提供适当的对比度，揭示每个特定成像组织中所有需要的临床细节，放射科医生必须四次查看单个 CT 切片：第一次查看关注肺窗；第二次查看关注软组织窗；第三次查看关注肝窗；第四次查看关注骨窗。为了增强进行全面诊断的能力，同时缩短诊断时间，我们开发了 BACCT（基于生物学的 CT 图像压缩扩展算法）方法。我们的算法将 HDR CT 图像压缩和扩展（压缩扩展）为单个低动态范围图像。在执行压缩扩展程序之前，需要进行独特的处理，包括增强和拉伸图像的操作。我们的算法已在大量 CT 体图像上进行了演示。在单个图像中，每个 CT 切片都显示了所有临床所需的 CT 信息。该算法以全自动的方式对 CT 图像进行压缩扩展。合作的放射科医生已经测试了我们的算法方法的结果，并报告说这些图像似乎提供了所有必要的信息。然而，仍需要进行统计可靠性的临床测试。
