Automatic cell segmentation in microscopic color images using ellipse fitting and watershed

Author

Park, M. ; Jin, J.S. ; Peng, Y. ; Summons, P. ; Yu, D. ; Cui, Y. ; Luo, S. ; Wang, F. ; Santos, L. ; Xu, M.

Author_Institution

Sch. of Design, Commun. & IT, Univ. of Newcastle, Callaghan, NSW, Australia

fYear

2010

fDate

13-15 July 2010

Firstpage

69

Lastpage

74

Abstract

This paper presents an efficient and innovative method for the automated counting of cells in a microscopic image. The performance of watershed-based algorithms for the segmentation of clustered cells has been well demonstrated. The strength of our algorithm lies in the fact that it incorporates knowledge of color in the image. Our method uses the watershed transform with iterative shape alignment and is shown to be more accurate in retaining cell shape. We report a sensitivity of 97% and specificity of 96% when all color bands are used. Our methods could be of value to computer-based systems designed to objectively interpret microscopic images, since they provide a means for accurate cell segmentation.

Keywords

cellular biophysics; image segmentation; medical image processing; microscopy; automatic cell segmentation; cell automated counting; cell shape; color bands; computer-based systems; ellipse fitting; iterative shape alignment; microscopic color images; watershed transform; watershed-based algorithms; Australia; Classification algorithms; Image edge detection; Image segmentation;

fLanguage

English

Publisher

ieee

Conference_Titel

Complex Medical Engineering (CME), 2010 IEEE/ICME International Conference on

Conference_Location

Gold Coast, QLD

Print_ISBN

978-1-4244-6841-6

Type

conf

DOI

10.1109/ICCME.2010.5558869

Filename

5558869