An automated method for gridding and clustering-based segmentation of cDNA microarray images

被引：26

作者：

Giannakeas, Nikolaos ^{[1
,2
]}

Fotiadis, Dimitrios I. ^{[1
,3
]}

机构：

[1] Univ Ioannina, Dept Comp Sci, Unit Med Technol & Intelligent Informat Syst, GR-45110 Ioannina, Greece

[2] Univ Ioannina, Sch Med, Biol Chem Lab, GR-45110 Ioannina, Greece

[3] Biomed Res Inst 4, Ioannina, Greece

来源：

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS | 2009年 / 33卷 / 01期

关键词：

Microarray image processing; Gridding; Segmentation; K-means; Fuzzy C means;

D O I：

10.1016/j.compmedimag.2008.10.003

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Microarrays are widely used to quantify gene expression levels. Microarray image analysis is one of the tools, which are necessary when dealing with vast amounts of biological data. In this work we propose a new method for the automated analysis of microarray images. The proposed method consists of two stages: gridding and segmentation. Initially, the microarray images are preprocessed using template matching, and block and spot finding takes place. Then, the non-expressed spots are detected and a grid is fit on the image using a Voronoi diagram. In the segmentation stage, K-means and Fuzzy C means (FCM) Clustering are employed. The proposed method was evaluated using images from the Stanford Microarray Database (SMD). The results that are presented in the segmentation stage show the efficiency of our Fuzzy C means-based work compared to the two already developed K-means-based methods. The proposed method can handle images with artefacts and it is fully automated. (C) 2008 Elsevier Ltd. All rights reserved.

引用

页码：40 / 49

页数：10

共 39 条

[1] Hybrid spot segmentation in four-channel microarray genotyping image data [J].

Abbaspour, Mohsen ;

Abugharbieh, Rafeef ;

Podder, Mohua ;

Tripp, Ben W. ;

Tebbutt, Scott J. .

2006 IEEE INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY, VOLS 1 AND 2, 2006, :11-16

[2] Microarray segmentation methods significantly influence data precision [J].

Ahmed, AA ;

Vias, M ;

Iyer, NG ;

Caldas, C ;

Brenton, JD .

NUCLEIC ACIDS RESEARCH, 2004, 32 (05) :e50

[3]

AURENHAMMER F, 1991, COMPUT SURV, V23, P345, DOI 10.1145/116873.116880

[4]

*AX INSTR, 1999, GENEPIX US GUID

[5] Gridline: Automatic grid alignment in DNA microarray scans [J].

Bajcsy, P .

IEEE TRANSACTIONS ON IMAGE PROCESSING, 2004, 13 (01) :15-25

[6]

Bezdek J. C., 1981, Pattern recognition with fuzzy objective function algorithms

[7] Mixture model analysis of DNA microarray images [J].

Blekas, K ;

Galatsanos, NP ;

Likas, A ;

Lagaris, IE .

IEEE TRANSACTIONS ON MEDICAL IMAGING, 2005, 24 (07) :901-909

[8] Unsupervised technique for robust target separation and analysis of DNA microarray spots through adaptive pixel clustering [J].

Bozinov, D ;

Rahnenführer, J .

BIOINFORMATICS, 2002, 18 (05) :747-756

[9]

Buckley M., 2000, SPOT USERS GUIDE

[10]

BUHLER J., 2000, Dapple: Improved techniques for finding spots on DNA microarrays

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