Segmentation of cell nuclei in images of renal biopsy samples

Author

Seminowich, Sansira ; Sar, Aylin ; Yilmaz, Serdar ; Rangayyan, Rangaraj M.

Author_Institution

Schulich Sch. of Eng., Dept. of Electr. & Comput. Eng., Univ. of Calgary, Calgary, AB, Canada

fYear

2010

fDate

2-5 May 2010

Firstpage

1

Lastpage

4

Abstract

Diagnosis and monitoring of kidney diseases and transplants is supported by microscopic analysis of needle-core biopsy samples. The current methods of analysis are affected by inconsistencies, bias, and inaccuracies. We propose and evaluate image processing methods for automatic segmentation of cell nuclei in digital images of renal biopsy samples. The methods evaluated include automatic thresholding, adaptive thresholding, and morphological granulometry. The results are compared to annotations made by an expert pathologist of more than 1500 cells in 18 images from different patients. The three methods provided true-positive ratios in the range 0.80 to 0.93.

Keywords

diseases; image segmentation; medical image processing; cell nuclei images segmentation; image processing methods; kidney diseases; morphological granulometry; needle core biopsy samples; pathologist; renal biopsy samples; Biomedical imaging; Image segmentation; Silver; Size measurement; cell nuclei; histopathology; image segmentation; needle-core renal biopsy;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering (CCECE), 2010 23rd Canadian Conference on

Conference_Location

Calgary, AB

ISSN

0840-7789

Print_ISBN

978-1-4244-5376-4

Electronic_ISBN

0840-7789

Type

conf

DOI

10.1109/CCECE.2010.5575162

Filename

5575162