Automation of Imaging Cytometry for Analysis of Natural Nanoplankton Populations

毕格罗海洋科学实验室的9423535名Sieracki研究人员将根据显微镜产生的数字图像的分析，进一步开发用于浮游植物细胞自动测量的成像细胞测量仪器--在这种情况下，荧光显微镜。通过对自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，以便更快地分析浮游生物样本，并减少对操作员干预的需要。该系统将通过硬件和软件相结合的方式进行改进。他们的荧光显微镜将增加一个计算机控制的电动工作台和新的双频或三频滤光片装置。还将开发用于图像采集和分析的新技术和算法。并将通过测试分类算法和使用神经网络技术，从数字图像数据中进行自动细胞分类的研究。该项目将促进对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.