A pipeline of image analysis algorithm is developed for automatic analysis and quantification of neurons in microscopic
images of zebrafish embryos. Key steps of pipeline include segmentation of zebrafish embryos from background,
detection of the ROI, and quantitative measurement of neurons in the ROI. First, morphological operations are used to
segment the zebrafish embryo from the background. Then based on the prior information that the torso has two
approximately parallel boundaries corresponding to the back and abdomen, the algorithm automatically creates a ROI
enclosing the torso. Finally, the number of neurons is obtained by improved Hough transform. Our results show that the
image analysis algorithm has a high accuracy and fast computational speed. Development of such an automated image
analysis pipeline represents a step toward high-throughput screening of zebrafish images with an accurate and
reproducible quantification of neurons.
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