| Author(s): |
Michael Grasso; Ronil Mokashi; Alden A. Dima; Antonio Cardone; Kiran Bhadriraju; Anne L. Plant; Mary C. Brady; Yaacov Yesha; Yelena Yesha; |
| Title: |
Image Classification of Vascular Smooth Muscle Cells |
| Published: |
November 11, 2010 |
| 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-cell and cell-to-matrix interactions. Analysis of these changes may be used to better understand how these interactions correspond to certain physiologic processes. |
| Proceedings: |
1st ACM International Health Informatics Symposium |
| Location: |
Arlington, VA |
| Dates: |
November 11-12, 2010 |
| Keywords: |
digital image processing, machine learning, molecular biology |
| Research Areas: |
Imaging |
| PDF version: |
 Click here to retrieve PDF version of paper (393KB) |
