ADAPTIVE SEGMENTATION OF CELLS AND PARTICLES IN FLUORESCENT MICROSCOPE IMAGE
Author(s):
M.Kanchana , Professor, Department of Information Technology, Karpaga Vinayaga College of Engineering & Technology, Chinna Kolambakkam, Madurantakam Taluk, Kanchipuram-603308, Tamil Nadu, India; H.Bharani, Assistant Professor, Department Of Information Technology, Karpaga Vinayaga College of Engineering & TechnologyKeywords:
Fluorescent Microscope Image, Adaptive SegmentationAbstract:
Understanding the mechanisms of cell motility and their regulation is an important challenge in biomedical research. The ability of cells to exert forces on their environment and alter their shape as they move is essential to various biological processes such as the immune response, embryonic development, or tumor genesis .Recent technological advances in con-focal fluorescence microscopy have given researchers the opportunity to investigate these complex processes in vivo. However, they also lead to a tremendous increase in the amount of image data acquired during the studies. Therefore, the analysis of time-lapse experiments relies increasingly on automated image processing techniques. Namely, there is a high demand for fast and robust methods to help biologists to quantitatively analyze time-lapse image data. The potential of the proposed tracking scheme and the advantages and disadvantages of both frameworks are demonstrated on 2-D and 3-D time-lapse series of rat adipose-derived mesenchymal stem cells and human lung squamous cell carcinoma cells, respectively. The crucial tasks are, in particular, segmenting, tracking, and evaluating movement tracks and morphological changes of cells, sub-cellular components and other particles.
Other Details:
| Manuscript Id | : | J4RV1I1023 |
| Published in | : | Volume : 1, Issue : 1 |
| Publication Date | : | 01/04/2015 |
| Page(s) | : | 1-6 |
