Stahl M, Aach T, Dippel S
Philips Research, Hamburg, Germany.
Med Phys. 2000 Jan;27(1):56-65. doi: 10.1118/1.598857.
Today's digital radiography systems mostly use unsharp maskinglike enhancement algorithms based on splitting input images into two or three frequency channels. This method allows fine detail enhancement as well as processing of global contrast (harmonization). However, structures of medium size are not accessible. In extension of a standard algorithm of such type, we develop and test a new enhancement algorithm based on hierarchically repeated unsharp masking, resulting in a multiscale architecture allowing consistent access to structures of all sizes. Our algorithm decomposes a radiograph by a pyramid-architecture, dividing it into eight or more channels representing structures of different sizes, known as "scales." At each scale, weakly contrasting structures are then enhanced by suitable nonlinear processing. We emphasize two points: first, backward compatibility to the standard algorithm which is used routinely in clinical practice. This allows reuse of current parametrization know-how as well as a smooth transition from current to new processing. Second, our enhancement is noise-resistant in the sense that it prevents unacceptable noise amplification. A prototype implementation of the algorithm is undergoing trials in the clinical routine of radiology departments of major German hospitals. Results strongly indicate the superior performance and high acceptance of the new processing.
如今的数字射线照相系统大多使用基于将输入图像分割为两个或三个频率通道的类非锐化掩膜增强算法。这种方法既可以进行细节增强，也可以处理全局对比度（协调）。然而，中等尺寸的结构无法得到处理。在扩展此类标准算法的基础上，我们开发并测试了一种基于分层重复非锐化掩膜的新增强算法，从而形成了一种多尺度架构，能够始终如一地处理各种尺寸的结构。我们的算法通过金字塔架构对射线照片进行分解，将其划分为八个或更多代表不同尺寸结构（即“尺度”）的通道。然后，在每个尺度上，通过适当的非线性处理来增强对比度较弱的结构。我们强调两点：第一，与临床实践中常规使用的标准算法向后兼容。这使得当前的参数设置知识能够得以复用，并且能够从当前处理平稳过渡到新的处理方式。第二，我们的增强算法具有抗噪性，即它能防止出现不可接受的噪声放大。该算法的原型实现正在德国各大医院放射科的临床常规工作中进行试验。结果有力地表明了这种新处理方式的卓越性能和高度可接受性。
