Phase Contrast Cell Segmentation Using Machine Learning Approach
نویسندگان
چکیده
In this paper, we present a machine learning approach based on random forest (RF) for automatic segmentation of living cells in phase contrast images. The proposed method is performed by a multistage classification working on both low and high level of the image. Pixel-wise classification is first performed to obtain a probability map of dark and bright cell regions. K-means clustering is then used to group pixels into candidate cell regions. Finally, another RF is called to verify the candidate cell regions. The experimental results show promising performance of the proposed method.
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