Segmentation and Classification of M-FISH Human Chromosome Images

Author

Lijiya, A. ; Sangeetha, M.K. ; Govindan, V.K.

Author_Institution

Dept. Of Comput. Sci. & Eng., Nat. Inst. of Technol., Calicut, India

fYear

2012

fDate

9-11 Aug. 2012

Firstpage

102

Lastpage

105

Abstract

Traditional analysis of chromosomes using gray scale images is a complex and tough task. With the advent of multi-spectral image acquisition since 1996, chromosome analysis becomes much easier using M-FISH (Multi-spectral Fluorescence In-Situ Hybridization) chromosome images. In this paper we present a majority voting for chromosome segmentation and fuzzy logic classifier for classification of M-FISH human chromosome images. Some noise removal techniques are also applied to improve segmentation and classification accuracy.

Keywords

fuzzy logic; image classification; image denoising; image segmentation; medical image processing; M-FISH human chromosome image classification; M-FISH human chromosome image segmentation; fuzzy logic classifier; gray scale images; multispectral fluorescence in-situ hybridization; multispectral image acquisition; noise removal techniques; Accuracy; Cells (biology); Fuzzy logic; Image edge detection; Image segmentation; Labeling; Chromosome; Classification; Fuzzy-Logic; M-FISH; Segmentation;

fLanguage

English

Publisher

ieee

Conference_Titel

Advances in Computing and Communications (ICACC), 2012 International Conference on

Conference_Location

Cochin, Kerala

Print_ISBN

978-1-4673-1911-9

Type

conf

DOI

10.1109/ICACC.2012.22

Filename

6305564