Grasso, M.
, Mokashi, R.
, Dima, A.
, Cardone, A.
, Bhadriraju, K.
, Plant, A.
, Brady, M.
, Yesha, Y.
and Yesha, Y.
(2010),
Image Classification of Vascular Smooth Muscle Cells, 1st ACM International Health Informatics Symposium , Arlington, VA, US, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=905981
(Accessed October 16, 2025)
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
Image Classification of Vascular Smooth Muscle Cells
Published
Author(s)
Michael Grasso, Ronil Mokashi , , , , , , Yaacov Yesha, Yelena Yesha
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 Title
1st ACM International Health Informatics Symposium
Conference Dates
November 11-12, 2010
Conference Location
Arlington, VA, US
Pub Type
Conferences
Download Paper
Keywords
digital image processing, machine learning, molecular biology
Citation
Issues
If you have any questions about this publication or are having problems accessing it, please contact [email protected].
Created November 10, 2010, Updated October 12, 2021