High Dynamic Range Microscopy for Cytopathological Cancer Diagnosis
High Dynamic Range Microscopy for Cytopathological Cancer Diagnosis
复制标题
用于细胞病理学癌症诊断的高动态范围显微镜
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
T. Aach
中科院分区：
文献类型：
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作者：
A. Bell;J. Brauers;J. Kaftan;D. Meyer;A. Böcking;T. Aach
癌症是最常见的死亡原因之一。细胞病理学，即基于细胞的癌症诊断可以应用于筛查场景，并允许早期和高度敏感的癌症检测，从而增加治愈的机会。本文讨论的细胞癌变的检测是基于明光显微镜。这些细胞通过安装在显微镜上的照相机成像，从而可以测量细胞的特性。然而，这些相机只有一个有限的动态范围，这往往使属性的量化困难，甚至不可能。因此，为了能够对显微镜图像进行计算机辅助分析，必须改进成像技术。为此，我们展示了如何通过获取一组不同曝光的细胞图像来增加动态范围。这些高动态范围（HDR）图像允许测量细胞特征，否则很难捕获，如果有的话。我们发现HDR显微镜不仅增加了动态范围，而且进一步降低了噪声，提高了颜色的采集。我们开发基于HDR显微镜的算法，这对于细胞病理学肿瘤学和早期癌症检测至关重要，并且只有通过HDR显微镜成像才能实现。我们显示某些亚细胞特征的检测，所谓的AgNORs，在银（Ag）染色标本。此外，我们给出了两个进一步应用的例子，即：1)免疫细胞化学制剂中染色细胞的检测和2)低对比度染色标本核分割的颜色分离。
Cancer is one of the most common causes of death. Cytopathological, i.e., cell-based, diagnosis of cancer can be applied in screening scenarios and allows an early and highly sensitive detection of cancer, thus increasing the chance for cure. The detection of cancer on cells addressed in this paper is based on bright field light microscopy. The cells are imaged with a camera mounted on a microscope, allowing to measure cell properties. However, these cameras exhibit only a limited dynamic range, which often makes the quantification of properties difficult or even impossible. Consequently, to allow a computer-assisted analysis of microscopy images, the imaging has to be improved. To this end, we show how the dynamic range can be increased by acquiring a set of differently exposed cell images. These high dynamic range (HDR) images allow to measure cellular features that are otherwise difficult to capture, if at all. We show that HDR microscopy not only increases the dynamic range, but furthermore reduces noise and improves the acquisition of colors. We develop HDR microscopy-based algorithms, which are essential for cytopathological oncology and early cancer detection and only possible with HDR microscopy imaging. We show the detection of certain subcellular features, so-called AgNORs, in silver (Ag) stained specimens. Furthermore, we give examples of two further applications, namely: 1) the detection of stained cells in immunocytochemical preparations and 2) color separation for nuclear segmentation of specimens stained with low contrast.