Abstract :
Modern technology has enabled monitoring of large populations of live cells over extended time periods in experimental settings. Live imaging of cell populations growing in a culture vessel has been widely adopted in biomedical experiments. Such experiments create large amount of time lapse images, and the information embedded in these images holds tremendous promise for scientific discovery. The growing amount of such data calls for automated or semi automated computer vision tools to detect and analyze the dynamic cellular processes, and to extract the information necessary for biomedical study. Live cells are often of low contrast with little natural pigmentation, therefore they usually need to be stained or fixed in order to be visible under bright field microscopy or florescence microscopy. However, fixing or staining may destroy the cells or introduce artifacts. Rakshitha K. S | Radhika K. R "Mitosis Detection in Phase Contrast Microscopy Image Sequences of Stem Cell Populations: A Critical Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-2 , February 2018, URL: https://www.ijtsrd.com/papers/ijtsrd9472.pdf Paper URL: http://www.ijtsrd.com/computer-science/database/9472/mitosis-detection-in-phase-contrast-microscopy-image-sequences-of-stem-cell-populations-a-critical-review/rakshitha-k-s
Keyword :
Time lapse image, Deep neural network, mitosis detection