Efficient segmentation framework of cell images in noise environments

EunSang Bak; Kayvan Najarian; John P Brockway

doi:10.1109/IEMBS.2004.1403538

Efficient segmentation framework of cell images in noise environments

Conf Proc IEEE Eng Med Biol Soc. 2004:2004:1802-5. doi: 10.1109/IEMBS.2004.1403538.

Authors

EunSang Bak¹, Kayvan Najarian, John P Brockway

Affiliation

¹ Electrical and Computer Engineering Department, University of North Carolina, Charlotte, NC 28223, USA.

PMID: 17272058
DOI: 10.1109/IEMBS.2004.1403538

Abstract

In this paper, we propose an efficient segmentation method that exploits local information for automated cell segmentation. This method introduces a new criterion function based on statistical structure of the objects in cell image. Each pixel is initially assigned to the most probable region and then the pixel assignment process is iteratively updated by a new criterion function until steady state is reached. We apply the proposed method to cervical cell images as well as the corresponding noisy images that are contaminated by Gaussian noise. The performance of the proposed method is evaluated based on the results from both normal and noisy cell images.