Automatic Microarray Spot Segmentation Using a Snake-Fisher Model

Author

Ho, Jinn ; Hwang, Wen-Liang

Author_Institution

Inst. of Inf. Sci. & Genomics Res. Center, Acad. Sinica, Taipei

Volume

27

Issue

6

fYear

2008

fDate

6/1/2008 12:00:00 AM

Firstpage

847

Lastpage

857

Abstract

Inspired by Paragious and Deriche´s work, which unifies boundary-based and region-based image partition approaches, we integrate the snake model and the Fisher criterion to capture, respectively, the boundary information and region information of microarray images. We then use the proposed algorithm to segment the spots in the microarray images, and compare our results with those obtained by commercial software. Our algorithm is automatic because the parameters are adaptively estimated from the data without human intervention.

Keywords

adaptive estimation; edge detection; genetics; image segmentation; medical image processing; adaptive estimation; automatic microarray spot segmentation; boundary-based image partition; gene expressions; microarray images; region-based image partition; snake-Fisher model; Microarray image; spot segmentation; Algorithms; Artificial Intelligence; Computer Simulation; Image Enhancement; Image Interpretation, Computer-Assisted; Microscopy, Fluorescence; Models, Theoretical; Oligonucleotide Array Sequence Analysis; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;

fLanguage

English

Journal_Title

Medical Imaging, IEEE Transactions on

Publisher

ieee

ISSN

0278-0062

Type

jour

DOI

10.1109/TMI.2008.915697

Filename

4427254