Image Processing

Much is made today, 制造商和用户的一致好评, 投影射线照相系统中采集设备的图像质量属性. Metrics such as Detective Quantum Efficiency have been developed to measure this quality on a quantitative, absolute scale. However, 由于图像采集设备之间的“原始”图像质量差异减小, 随着这些设备开始接近它们的理论极限, 医疗成像链中的其他元素将变得越来越重要.

图像处理就是这样一个元素. 事实上，它是一个关键因素. 图像处理可以取一个勉强可以接受的图像采集系统的输出, 并使其定性地适合于诊断目的. On the other hand, 图像处理也会使一个优秀的图像采集设备的输出变得无用. Image processing must be done right in order for the complete imaging system to be clinically useful, 但是“right”在不同的应用中可以有不同的含义.

It is foolhardy to view or interpret a diagnostic image without an awareness and understanding of the image processing techniques that were used to produce it. This does not mean that one must become an imaging scientist or algorithm developer to view or interpret digital medical images. However, being able to recognize and appreciate the sometimes subtle effects of image processing can help the viewer to separate anatomy and physiology from art and artifact.

医学图像处理大致可分为三代. 第一代可以追溯到银幕/胶片(S/F)成像的早期. 每种类型的薄膜都有特定的特征响应曲线(称为D-logE曲线), 因为这是一个光学图 D密度对对数 Exposure; also known as the H&D曲线后两位研究者, 费迪南德·赫特和维罗·查尔斯·德里菲尔德, 是谁在19世纪末首次引入它的?.

这条s型曲线描述了x射线曝光(以及x射线曝光的变化), 有时被称为主体, 或辐射对比度)转换成光密度(以及光密度的变化, 有时也称为放射造影剂). The shape of the curve, 这也取决于化学处理条件, 提供特定影片类型的视觉“外观”. 例如，高对比度的胶片具有陡峭、狭窄的H&D曲线，而“纬度”，或低对比度胶片的曲线较宽，斜率较低. 正确的薄膜取决于应用的需要, 以及观众的诊断偏好.

随着医学成像数字时代的到来(1970年代末和1980年代初), 第一代扩展到包括基于计算机的图像处理技术. 除了更大程度的控制信号幅度(例如, 使用直方图、窗口宽度和水平调整), 图像处理开始使用图像信号的空间频率作为变量. For example, higher spatial frequencies could be used to adjust the visibility of small structures and the visibility of image noise, 而较低的空间频率对较大结构的出现贡献更大.

Edge enhancement (the most familiar algorithm in this class being unsharp masking ) and noise reduction are examples of the new digital tools that were now part of the 1st-generation image processing arsenal. 加工技术可以由制造商(或用户)调整!)，为每个身体部位/投影或应用产生首选的“外观”. 这些相对简单、经过验证的技术至今仍在某些系统中使用.

The desire for even greater control of image appearance led to the 2nd generation of image processing techniques. 第二代的算法比前几年更加复杂和复杂. 第二代技术的一个例子是多尺度处理, in which the original image is decomposed into a collection (up to 12 in some systems) spatial-frequency ranges. 每个范围都可以进行不同的处理, 为用户提供定制每个身体部位的输出“外观”的能力, projection, or special application. The 2nd generation requires a good deal of user input and iterative on-site visual optimization in order to determine the many processing parameters for each image type. 只有这样，图像处理的性能才能针对每个用户或站点进行优化.

This exquisite control of image display properties has become the hallmark of modern digital imaging systems, 但它也带来了“阴暗面”," namely, 需要知道你到底在做什么. As noted, 做相关的解剖是很容易的, 生理和病理在图像处理后消失. It is much more difficult to figure out how to enhance just the right structures to provide the optimum diagnostic presentation to the viewer. 医疗成像制造商继续花费大量时间, effort and money developing robust image processing algorithms that provide a net benefit in the applications in which they are used.

第三代图像处理才刚刚开始. One major goal of this generation is to eliminate the need for extensive user input and interaction, 前几代人的主要缺点之一. 最终的图像应该只是“出现”在输出设备上, 具有优化诊断解释所需的属性. This simple concept requires an even greater degree of complexity and sophistication in the processing algorithms. 一些新的算法已经可以自主运行了.e., 无需用户干预), 创建不仅优化图像显示, but, as a by-product, a smoother, 更高效的工作流程, 这使得用户更关注病人而不是图像. This 3rd generation of image processing must be "intelligent" enough to analyze the content of each input image, 并决定如何最好地呈现临床相关的细节. 自动身体部位识别等功能, 自动准直识别, and application-specific processing-parameter setting fall into the category of 3rd-generation image processing.

下面是一组图像，说明了不同时代的图像处理. 注意细节可见性的差异, 灰度复制和代际间的人工制品.

Image Sets

Chest

人类胸部图像是图像处理中最困难的挑战之一. 胸部图像往往有很大的曝光动态范围, 图像明暗区域的临床相关细节, 以及各种可能的细微而明显的病症, 所有这些都必须正确显示, 这些都不为人所知 a priori.

对于S/F系统来说，满足这些不同的要求尤其困难. Over the past century, film manufacturers have spent considerable resources trying to design the perfect S/F system for chest imaging. 数字成像系统, 他们天生的习得分离, processing and display, 为更清洁的解决方案提供机会. In particular, 与S/F系统相比，它们更宽的采集纬度可以捕获更多的信息, which must simultaneously act as capture medium (wide latitude important) and display medium (contrast important).

Image processing can then take the acquired data and attempt to present them for optimal interpretation. 随附的图像显示了四种不同的降低分辨率, 同样的原始CR胸部图像的处理版本, 连同每个图像的小部分在其原生分辨率.

第一代- S/F“Look”

1st Generation (digital) - Unsharp Masking (Edge Enhancement - program boosts contrast of higher spatial frequencies relative to lower spatial frequencies, 根据用户/制造商为应用程序选择的频率阈值)

2nd Generation - Multiscale algorithm for contrast adjustment (program adjusts local contrast in multiple spatial frequency ranges, 由用户/厂家选择的输入参数决定)

3rd Generation - Intelligent multiscale algorithm (no user intervention needed - program analyzes image in multiple spatial frequency ranges and optimizes display for both soft tissues and skeletal details automatically)

Knee

四肢成像不仅需要骨骼结构的高分辨率, 但也有能力观察软组织的细微对比变化一直到皮肤线. 由于它们相对较窄的曝光纬度，这对于大多数S/F系统来说是困难的. 当骨骼形成最佳对比时, 皮肤线附近的软组织通常颜色太深, 需要使用“热灯”."

数字成像系统, 他们的独立收购, 处理和显示功能, 提供一个潜在的解决方案. The ability to adjust image processing to the characteristics of the input image provides increased flexibility in the final display for interpretation. 随附的图像显示了四种不同的降低分辨率, 相同的原始CR膝盖图像的处理版本, 连同每个图像的小部分在其原生分辨率.

第一代- S/F“Look”

2nd Generation - Multiscale algorithm for contrast adjustment (program adjusts local contrast in multiple spatial frequency ranges, 由用户/厂家选择的输入参数决定)

Ankle

The superposition of bony structures (low x-ray transmission) can make it difficult to visualize soft tissues on S/F. 数字系统具有更宽的曝光纬度和图像处理能力，可以提供帮助. 随附的图像显示了四种不同的降低分辨率, 同样的原始CR脚踝图像的处理版本, 连同每个图像的小部分在其原生分辨率.

第一代- S/F“Look”

2nd Generation - Multiscale algorithm for contrast adjustment (program adjusts local contrast in multiple spatial frequency ranges, 由用户/厂家选择的输入参数决定)

Skull

The skull also presents a large dynamic range for display - much of the soft tissue around the skull, such as the nose, is usually difficult to see without special processing (even a "hot light" may not be able to reveal this area of high relative exposure in a S/F image). 随附的图像显示了四种不同的降低分辨率, 同样的原始颅骨图像的处理版本, 连同每个图像的小部分在其原生分辨率.

第一代- S/F“Look”

2nd Generation - Multiscale algorithm for contrast adjustment (program adjusts local contrast in multiple spatial frequency ranges, 由用户/厂家选择的输入参数决定)

小儿脊柱(后期)

侧脊柱由于其非常宽的动态范围，是一个非常难以捕捉的检查. In S/F systems, soft tissue is frequently "burned out" near the skin line due to the range of x-ray exposures involved, 最主要的需要是可视化骨骼的细节. In addition, the (dark) overlapping lungs behind the hemi-diaphragms can make details in the spine difficult to see. 随附的图像显示了四种不同的降低分辨率, 同一原始CR儿童脊柱图像的处理版本, 连同每个图像的小部分在其原生分辨率.

第一代- S/F“Look”

1st Generation (digital)- Unsharp Masking (Edge Enhancement - program boosts contrast of higher spatial frequencies relative to lower spatial frequencies, 根据用户/制造商为应用程序选择的频率阈值)

2nd Generation - Multiscale algorithm for contrast adjustment (program adjusts local contrast in multiple spatial frequency ranges, 由用户/厂家选择的输入参数决定)

胸部幻影-剂量系列

剂量和图像处理之间存在相互作用. 在较低的剂量水平下，图像的信噪比(SNR)下降(它们看起来更嘈杂)。. 增加这些图像的对比度, 全局或多个空间频带, 还能增加噪音的印象吗, 降低主观图像质量. 因此，在较低剂量下进行图像处理的能力往往受到限制.

Unfortunately, 许多图像处理算法以相同的方式处理所有图像, and, thus, 在低剂量图像上做得不好. Algorithms that measure local image SNR can do a better job of adjusting the extent of processing so as to avoid degradation in subjective image quality. Modern (3rd generation, and some 2nd generation) programs can adapt their processing to the local (or global) SNR of the image being processed.

随附的图像显示了在三种不同剂量水平下暴露的胸部幻像.5毫安、4毫安和32毫安，均为同一kV(125千伏). 每个剂量水平用1 -处理, 2nd-, 第三代处理算法(S/F“look”(上图)), 需要用户输入参数的多尺度技术(中), and an intelligent multiscale technique that sets its own parameters based on image analysis (bottom)).

正如预期的那样，噪声外观随着剂量的增加而改善(信噪比正在增加)。. However, the 1st-generation, 类似S/ f的显示在三种剂量水平下产生基本相同的放射成像对比度, 哪个符合其特征响应的固定形状. 随着剂量的增加，第二代算法也保持大致相同的细节对比度. 随着剂量的增加，第三代技术能够改善细节对比度, 调整其处理以提高信噪比. In fact, the detail visibility of the 3rd generation technique at lower dose levels can be better than that of the 2nd- or 1st generation techniques at higher doses. 这增加了在获取期间减少患者剂量的可能性, 并允许图像处理技术智能地补偿较差的信噪比, 同时仍然提供诊断有用的输出图像.

Analog (i.e., 基于胶片的边缘增强方法, 例如，在20世纪30年代，在印刷的半色调应用中已经使用了不锐利的掩蔽. 它们在医学图像处理中的应用直到半个世纪后才出现.