Monitoring Cell Volume and Growth Rate of Budding Yeast Based on Computer Vision Algorithm
Budding yeast,the scientific name of which is Saccharomyces cerevisiae,is a typical model organism for cell aging studies.High-throughput microfluidic devices,as long-term monitoring and analysis platforms to investigate cell dynamics along yeast replicative aging,usually encounter challenges in processing high-throughput micrographs.To address the challenges,such as the substantial com-putational load and limited data tolerance in image processing for extracting single-cell morphological parameters of budding yeast,an al-gorithm based on computer vision is proposed to extract mother-cell contours in single-cell traps.The algorithm integrates Canny edge detection,Hough transform,morphological operations,and linear interpolation.Several tailored optimizations have been implemented to deal with errors in contour extraction and enhance overall efficiency in image processing.Furthermore,the proposed algorithm is utilized to achieve high-precision automated extraction of cell volume and growth rate of budding yeast,and analyze the dynamic changes in cell volume during the process of yeast replicative aging and its correlation with replication lifespan.
万方数据
维普
