Integration of Raman Spectroscopy, On-Line Microscopic Imaging and Deep Learning-Based Image Analysis for Real-Time Monitoring of Cell Culture Process
文献类型： 会议论文
第一作者： Xiaoli Wang
作者： Xiaoli Wang 1 ; Guangzheng Zhou 1 ; Xue Zhong Wang 1 ;
作者机构： 1.Beijing Key Laboratory of Enze Biomass Fine Chemicals, College of New Materials and Chemical Engineering, Beijing Institute of Petrochemical Technology, Beijing 102617, China
关键词： Image Analysis;Deep Learning;Process Analytical Technology;Cell Culture;Raman Spectroscopy
会议名称： [ "International Conference on Intelligence Science" , "International conference on intelligence science"]
主办单位：
页码： 248-256
摘要： Traditionally, condition monitoring of mammalian cell culture processes is based on sampling and off-line analysis, which is labour intensive, time consuming, and causes time delays. In this work, in situ microscope and on-line Raman spectroscopy are investigated for simultaneous measurement of multiple properties of the cell growth state and biochemical indices of suspended animal cells. The focus is on investigation of deep learning-based Mask R-CNN algorithm for image analysis. The model is trained by 184 images with 183,040 cells using data augmentation methods and transfer learning technique. Mask R-CNN segments the clustered cells more effectively than the conventional one combining edge detection, intensity thresholding, and advanced watershed method. The evolution of geometrical features of cells is further analyzed, including equivalent diameter, circularity, and aspect ratio. It demonstrates the great potential of deep learning in the analysis of on-line images for control of the cell culture process.
分类号： tp18
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