Co-Restoring Multimodal Microscopy Images
We propose a novel microscopy image restoration algorithm capable of co-restoring Phase Contrast and Differential Interference Contrast (DIC) microscopy images captured on the same cell dish simultaneously. Cells with different phase retardation and DIC gradient signals are restored into a single image without the halo artifact from phase contrast or pseudo 3D shadow-casting effect from DIC. The co-restoration integrates the advantages of two imaging modalities and overcomes the drawbacks in single-modal image restoration. Evaluated on a datasets of five hundred pairs of phase contrast and DIC images, the co-restoration demonstrates its effectiveness to greatly facilitate the cell image analysis tasks such as cell segmentation and classification.
M. Li and Z. Yin, "Co-Restoring Multimodal Microscopy Images," Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9351, pp. 242-250, Springer Verlag, Oct 2015.
The definitive version is available at https://doi.org/10.1007/978-3-319-24574-4_29
Keywords and Phrases
Algorithms; Cells; Classification (of Information); Cytology; Image Reconstruction; Image Segmentation; Medical Computing; Restoration; Cell Image Analysis; Cell Segmentation; Differential Interference Contrast Microscopy; Imaging Modality; Microscopy Images; Multimodal Microscopy; Phase Contrasts; Phase Retardation; Medical Imaging
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