Souto M, Correa J, Tahoces P G, Tucker D, Malagari K S, Vidal J J, Fraser R G
Department of Radiology, Hospital General de Galicia, University of Santiago de Compostela, Spain.
J Digit Imaging. 1992 Nov;5(4):223-9. doi: 10.1007/BF03167803.
Postprocessing of the image data is an exciting capability of digital radiography that may improve diagnostic performance. We present a new algorithm that selectively enhances edges and contrast in both lungs and mediastinum while minimally amplifying noise in chest images. Using different size kernels, two smoothed images are generated from the original chest image. The two regions of interest (lungs and mediastinum) are identified based on the distribution of pixel values in the image. A modified nonlinear unsharp mask subtraction technique is then applied. The resulting image has enhanced high- and middle-frequency information in the mediastinum without distorting lung parenchyma or significantly enhancing noise. We consider that the technique employed in this study could be suitable for routine use although its true effectiveness in improving diagnostic accuracy awaits observer-performance evaluation that is currently under way.
图像数据的后处理是数字放射成像一项令人兴奋的功能，它可能会提高诊断性能。我们提出了一种新算法，该算法能在最小化放大胸部图像噪声的同时，有选择地增强双肺和纵隔的边缘及对比度。使用不同大小的内核，从原始胸部图像生成两幅平滑图像。基于图像中像素值的分布识别出两个感兴趣区域（肺和纵隔）。然后应用一种改进的非线性锐化掩模减法技术。所得图像增强了纵隔中的高频和中频信息，而不会扭曲肺实质或显著增强噪声。我们认为本研究中采用的技术可能适用于常规使用，尽管其在提高诊断准确性方面的真正有效性有待目前正在进行的观察者性能评估。
