Title :
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
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;
Conference_Titel :
Electrical and Computer Engineering (CCECE), 2010 23rd Canadian Conference on
Conference_Location :
Calgary, AB
Print_ISBN :
978-1-4244-5376-4
Electronic_ISBN :
0840-7789
DOI :
10.1109/CCECE.2010.5575162
