Automation of Imaging Cytometry for Analysis of Natural Nanoplankton Populations

Bigelow海洋科学实验室的研究人员将进一步开发成像细胞仪，用于基于显微镜产生的数字图像分析的浮游植物细胞的自动测量，在这种情况下是荧光显微镜。通过对天然浮游生物种群的自动分析，成像细胞术在解决生物海洋学中的基本问题方面具有很大的潜力。这项工作将增强Bigelow的显微成像系统，以便更快速地分析浮游生物样本，并减少操作员干预的需要。该系统将通过硬件和软件的结合进行改进。一个计算机控制的，电动舞台和新的双或三波段光学滤光片组将添加到他们的荧光显微镜。还将开发用于图像采集和分析的新技术和算法。通过测试分类算法和使用神经网络技术，研究从数字图像数据中自动进行细胞分类。该项目将促进海洋浮游生物群落营养和大小结构的研究。

9423535 Sieracki Researchers at the Bigelow Laboratory for Ocean Sciences will further develop imaging cytometry instrumentation for the automated measurement of phytoplankton cells based on the analysis of digital images produced by microscopy - in this case epifluorescence microscopy. Imaging cytometry has much potential for addressing basic questions in biological oceanography through the automated analysis of natural plankton populations. Work will enhance Bigelow's microscopic imaging system for more rapid analysis of plankton samples and reduce the need for operator intervention. The system will be improved through a combination of hardware and software. A computer-controlled, motorized stage and new dual or triple-band optical filter sets will be added to their epifluorescence microscope. New techniques and algorithms will also be developed for image acquisition and analysis. And research will be undertaken on automated cell classification from digital image data by testing classification algorithms and by using neural net techniques. The project will facilitate the study of oceanic plankton community trophic and size structures.