A multiscale graph cut approach to bright-field multiple cell image segmentation using a Bhattacharyya measure

Soo Min Kang; Justin W. L. Wan

doi:10.1117/12.2007002

13 March 2013 A multiscale graph cut approach to bright-field multiple cell image segmentation using a Bhattacharyya measure

Soo Min Kang, Justin W. L. Wan

Author Affiliations +

Proceedings Volume 8669, Medical Imaging 2013: Image Processing; 86693S (2013) https://doi.org/10.1117/12.2007002
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Automatic segmentation of bright-field cell images is important to cell biologists, but is difficult to achieve due to the complex nature of the cells in bright-field images (poor contrast, broken halo, missing boundaries). The standard segmentation techniques, such as the level set method and active contours, are not able to overcome these features of bright-field images. Consequently, poor segmentation results are produced. In this paper, we present a robust segmentation method, which combines the techniques of graph cut, multiresolution, and Bhattacharyya measure, performed in a multiscale framework, to locate multiple cells in bright-field images. The issue of low contrast in bright-field images is addressed by determining the difference in intensity profiles of the cells and the background. The resulting segmentation on the entire image frame provides global information. Then a local segmentation at different regions of interest is performed to obtain finer details of the segmentation result. We illustrate the effectiveness of the method by presenting the segmentation results of C2C12 (muscle) cells in bright-field images.

Citation Download Citation

Soo Min Kang and Justin W. L. Wan "A multiscale graph cut approach to bright-field multiple cell image segmentation using a Bhattacharyya measure", Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86693S (13 March 2013); https://doi.org/10.1117/12.2007002

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available