Restoring Artifact-Free Microscopy Image Sequences
Phase contrast and differential interference contrast, which are used to capture microscopy images of living cells, contain a few artifacts such as halo and shadow-cast effect. Removing these artifacts from microscopy images facilitates automated microscopy image analysis, such as the cell segmentation that is a critical step in cell tracking systems. We propose a restoration algorithm based on the microscopy imaging model and consider temporal consistency when restoring time-lapse microscopy image sequences. The artifact-free microscopy images are restored by minimizing a regularized quadratic cost function that is adaptable to input image properties. Our method achieves high segmentation accuracy and low computational cost compared to the previous methods.
Z. Yin and T. Kanade, "Restoring Artifact-Free Microscopy Image Sequences," Proceedings of the International Symposium on Biomedical Imaging (2017, Quebec City, Canada), pp. 909-913, Institute of Electrical and Electronics Engineers (IEEE), Mar 2011.
The definitive version is available at http://dx.doi.org/10.1109/ISBI.2011.5872551
International Symposium on Biomedical Imaging (2017: Sept. 11-13, Quebec City, Canada)
Keywords and Phrases
Automated Microscopy; Cell Segmentation; Cell Tracking System; Computational Costs; Critical Steps; Differential Interference Contrast; Input Image; Living Cell; Microscopy Image Analysis; Microscopy Images; Microscopy Imaging; Phase Contrasts; Quadratic Cost Functions; Restoration Algorithm; Segmentation Accuracy; Temporal Consistency; Time-Lapse Microscopy; Image Analysis; Image Reconstruction; Medical Imaging; Restoration; Image Segmentation; Image Restoration; Phase Contrast
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