Image classification of vascular smooth muscle cells
Pages 484 - 486
Abstract
The traditional method of cell microscopy can be subjective, due to observer variability, a lack of standardization, and a limited feature set. To address this challenge, we developed an image classifier using a machine learning approach. Our system was able to classify cytoskeletal changes in A10 rat smooth muscle cells with an accuracy of 85% to 99%. These cytoskeletal changes correspond to cell-to-matrix interactions. Analysis of these changes may be used to better understand how these interactions correspond to certain physiologic processes.
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Index Terms
- Image classification of vascular smooth muscle cells
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November 2010
886 pages
ISBN:9781450300308
DOI:10.1145/1882992
- Editor:
- Tiffany Veinot,
- General Chairs:
- Ümit V. Çatalyürek,
- Gang Luo,
- Program Chairs:
- Henrique Andrade,
- Neil R. Smalheiser
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Published: 11 November 2010
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IHI '10
IHI '10: ACM International Health Informatics Symposium
November 11 - 12, 2010
Virginia, Arlington, USA
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