Abstract:
:Phase contrast, a noninvasive microscopy imaging technique, is widely used to capture time-lapse images to monitor the behavior of transparent cells without staining or altering them. Due to the optical principle, phase contrast microscopy images contain artifacts such as the halo and shade-off that hinder image segmentation, a critical step in automated microscopy image analysis. Rather than treating phase contrast microscopy images as general natural images and applying generic image processing techniques on them, we propose to study the optical properties of the phase contrast microscope to model its image formation process. The phase contrast imaging system can be approximated by a linear imaging model. Based on this model and input image properties, we formulate a regularized quadratic cost function to restore artifact-free phase contrast images that directly correspond to the specimen's optical path length. With artifacts removed, high quality segmentation can be achieved by simply thresholding the restored images. The imaging model and restoration method are quantitatively evaluated on microscopy image sequences with thousands of cells captured over several days. We also demonstrate that accurate restoration lays the foundation for high performance in cell detection and tracking.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Yin Z,Kanade T,Chen Mdoi
10.1016/j.media.2011.12.006subject
Has Abstractpub_date
2012-07-01 00:00:00pages
1047-62issue
5eissn
1361-8415issn
1361-8423pii
S1361-8415(12)00003-5journal_volume
16pub_type
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