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Application of particle analysis to transmission electron microscopy (TEM)

机译:粒子分析在透射电子显微镜(TEM)中的应用

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Nanoparticles, particles with a diameter of 1-100 nanometers (nm), are of interest in many applications including device fabrication, quantum computing, and sensing because their size may give them properties that are very different from bulk materials. Further advancement of nanotechnology cannot be obtained without an increased understanding of nanoparticle properties such as size (diameter) and size distribution frequently evaluated using transmission electron microscopy (TEM). In the past, these parameters have been obtained from digitized TEM images by manually measuring and counting many of these nanoparticles, a task that is highly subjective and labor intensive. More recently, computer imaging particle analysis has emerged as an objective alternative by counting and measuring objects in a binary image. This paper will describe the procedures used to preprocess a set of gray scale TEM images so that they could be correctly thresholded into binary images. This allows for a more accurate assessment of the size and frequency (size distribution) of nanoparticles. Several preprocessing methods including pseudo flat field correction and rolling ball background correction were investigated with the rolling ball algorithm yielding the best results. Examples of particle analysis will be presented for different types of materials and different magnifications. In addition, a method based on the results of particle analysis for identifying and removing small noise particles will be discussed. This filtering technique is based on identifying the location of small particles in the binary image and removing them without affecting the size of other larger particles.
机译:纳米颗粒,直径为1-100纳米(NM)的颗粒,许多应用是感兴趣的,包括装置制造,量子计算和感测,因为它们的尺寸可以给它们与散装材料非常不同的性质。不能在使用透射电子显微镜(TEM)经常评估的尺寸(直径)和尺寸分布的纳米粒子特性的增加而不会增加纳米技术的进一步提高纳米技术的进一步推进。在过去,通过手动测量和计算许多这些纳米颗粒,这是一种非常主观和劳动密集的任务,已经从数字化TEM图像获得了这些参数。最近,通过计数和测量二进制图像中的物体,计算机成像粒子分析作为目标替代物。本文将描述用于预处理一组灰度TEM图像的过程,以便它们可以正确地阈值阈值为二进制图像。这允许更准确地评估纳米颗粒的尺寸和频率(尺寸分布)。采用轧制球算法研究了几种包括伪平场校正和滚动球背景校正的预处理方法,产生了最佳效果。颗粒分析的实例将出于不同类型的材料和不同的放大倍数。另外,将讨论基于用于识别和去除小噪声粒子的粒子分析结果的方法。该滤波技术基于识别二值图像中的小颗粒的位置并在不影响其他较大颗粒的尺寸的情况下去除它们。

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