Nuclei segmentation from breast cancer histology images

Author

Nikam, Akshay ; Gopal, Aarthi

Author_Institution

Shresh Gyan Vihar Univ. Jaipur, Jaipur, India

fYear

2013

fDate

13-14 Sept. 2013

Firstpage

18

Lastpage

22

Abstract

Histology image analysis using computer-aided diagnosis systems has become increasingly important during the last years. One reason is the need to alleviate the heavy workload of medical experts. In this paper, we introduce a general purpose framework which is able to segmentation of cell nuclei from microscopic images based on graph based segmentation and threshold methods.

Keywords

biomedical optical imaging; cancer; cellular biophysics; feature extraction; graph theory; image classification; image segmentation; medical image processing; microscopes; breast cancer histology image analysis; cell classification; cell extraction; cell nuclei segmentation; computer- aided diagnosis systems; graph based segmentation; medical expert workload; microscopic images; threshold methods; Breast cancer; Clustering algorithms; Histograms; Image edge detection; Image segmentation; Medical diagnostic imaging; Breast cancer; Graph Based Segmentation; Thresholding;

fLanguage

English

Publisher

ieee

Conference_Titel

Emerging Trends and Applications in Computer Science (ICETACS), 2013 1st International Conference on

Conference_Location

Shillong

Print_ISBN

978-1-4673-5249-9

Type

conf

DOI

10.1109/ICETACS.2013.6691387

Filename

6691387