Red blood cell segmentation from SEM images

Author

Vromen, Joost ; McCane, Brendan

Author_Institution

Human Media Interaction, Univ. of Twente, Enschede, Netherlands

fYear

2009

fDate

23-25 Nov. 2009

Firstpage

44

Lastpage

49

Abstract

We present a model based contour tracing approach to the problem of automatically segmenting a scanning electron microscope image of red blood cells. We use a second order polynomial model and a simple Bayesian approach to ensure smooth boundaries, and a postprocess ellipse fitting procedure to cull noise contours. Of all contours detected, 95.7% are correct, with a 0.6% false negative rate, and 4.3% false positive rate on 100 sample images involving more than 11000 red blood cells.

Keywords

blood; cellular biophysics; edge detection; image segmentation; medical image processing; polynomials; scanning electron microscopy; Bayesian approach; SEM images; contour detection; ellipse fitting; image segmentation; model-based contour tracing; red blood cell segmentation; scanning electron microscope; second order polynomial model; Cells (biology); Clustering algorithms; Diseases; Image edge detection; Image segmentation; Morphology; Multiple sclerosis; Red blood cells; Scanning electron microscopy; Shape;

fLanguage

English

Publisher

ieee

Conference_Titel

Image and Vision Computing New Zealand, 2009. IVCNZ '09. 24th International Conference

Conference_Location

Wellington

ISSN

2151-2205

Print_ISBN

978-1-4244-4697-1

Electronic_ISBN

2151-2205

Type

conf

DOI

10.1109/IVCNZ.2009.5378364

Filename

5378364