Umest Adiga P S, Chaudhuri B B
Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, Calcutta, India.
Micron. 2000 Jan;31(1):5-15. doi: 10.1016/s0968-4328(99)00057-8.
In this paper we have presented a semi-automatic method for segmenting and counting the Fluorescence In Situ Hybridization (FISH) signals per cell nucleus in a 3D tissue image. The number of FISH signals indicate the gain (trisomy) or loss (monosomy) of certain base-sequences in deoxyribonucleic acid (DNA). The quantitative evaluation of the loss or gain in DNA is necessary in qualitative diagnostic molecular pathology. Multispectral volumetric images are obtained using the Confocal Microscope. Each consists of a red channel depicting the 3D morphology of the tissue and green channel containing the FISH signals. The red channel tissue image is segmented first to determine the membership of the FISH signal to a particular nuclei. Various segmentation methods starting from simple local thresholding to volume growing and active volumes are used for segmentation. A brief comparative study of the visual signal count by pathologist and our automatic count is also presented.
在本文中，我们提出了一种半自动方法，用于在三维组织图像中分割和计数每个细胞核中的荧光原位杂交（FISH）信号。FISH信号的数量表明脱氧核糖核酸（DNA）中某些碱基序列的增加（三体性）或减少（单体性）。在定性诊断分子病理学中，对DNA增减进行定量评估是必要的。使用共聚焦显微镜获取多光谱体积图像。每个图像都由一个描绘组织三维形态的红色通道和一个包含FISH信号的绿色通道组成。首先对红色通道的组织图像进行分割，以确定FISH信号属于哪个特定的细胞核。从简单的局部阈值分割到体积生长和活动体积等各种分割方法都用于分割。还给出了病理学家视觉信号计数与我们自动计数的简要对比研究。
