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Publication Citation: Image Classification of Vascular Smooth Muscle Cells

NIST Authors in Bold

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: PDF Document Click here to retrieve PDF version of paper (402KB)