线虫是生命科学研究领域非常重要的模式生物，在衰老等许多研究中被广泛使用。它体积小，身长约一毫米，使用线虫进行科学实验，传统的方法是通过肉眼观察显微镜下大量的线虫，工作十分繁重。由于拍摄得到的线虫实验图像存在亮度不均、难于处理等问题，目前还没有很好的线虫实验图像处理和特征计算方法可以让研究者方便的对各自实验室产出的线虫实验图像进行自动的图像分割以及表型定量。本项目首先设计专门的图像分割算法将线虫从实验图像中提取出来；然后设计相应的数学方法对线虫的形态进行数学表示，并用于对形式各异的线虫表型特征进行计算。设计定量的线虫表型特征包括：线虫大小、长宽、颜色、运动活力、荧光强度及分布、脂肪酸分布等表型。并通过处理线虫整个生命周期中的实验图像，定量分析线虫的各种表型在衰老过程中的变化趋势。本研究将为线虫的形态描述提供数学支撑、并设计线虫衰老表型定量方法，从而为系统的进行线虫衰老组学研究提供量化指标。

Nematode is a very important model organism in the field of life science research and is widely used in many studies such as aging. It is small in size and about one millimeter in length. When using nematodes for scientific experiments, the traditional method is to observe a large number of nematodes under the microscope by the naked eye, which is a heavy task. Due to the uneven brightness and difficult processing of the nematode experimental images, there is no systematic nematode experimental image processing software that allows researchers to easily perform automatic image segmentation on the nematode experimental images produced by their respective laboratories. This project designed a special image segmentation algorithm for the uneven brightness of the nematode experimental images, designed the mathematical representation of nematode morphology, and developed a set of nematode experimental video and image analysis software for image segmentation and phenotyping of different types of nematode experimental images. The planned quantitative phenotypes include nematode phenotypes such as nematode size, length and width, color, athletic activity, fluorescence intensity and distribution, fatty acid content and distribution. It is planned to collect experimental videos and images of the nematode throughout its life cycle, and quantitatively analyze the various phenotypes of nematodes with the growth trend of nematodes and aging. Therefore, the quantitative description of the changes of various phenotypes of nematodes in the aging process provides quantitative indicators for the systematic study of nematode aging.