Literature DB >> 18541491

Automatic microarray spot segmentation using a Snake-Fisher model.

Jinn Ho1, Wen-Liang Hwang.   

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.

Entities:  

Mesh:

Year:  2008        PMID: 18541491     DOI: 10.1109/TMI.2008.915697

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  5 in total

1.  Low-complexity PDE-based approach for automatic microarray image processing.

Authors:  Bogdan Belean; Romulus Terebes; Adrian Bot
Journal:  Med Biol Eng Comput       Date:  2014-10-29       Impact factor: 2.602

2.  Unsupervised image segmentation for microarray spots with irregular contours and inner holes.

Authors:  Bogdan Belean; Monica Borda; Jörg Ackermann; Ina Koch; Ovidiu Balacescu
Journal:  BMC Bioinformatics       Date:  2015-12-23       Impact factor: 3.169

3.  Fully Automated Complementary DNA Microarray Segmentation using a Novel Fuzzy-based Algorithm.

Authors:  Hamidreza Saberkari; Sheyda Bahrami; Mousa Shamsi; Mohammad Javad Amoshahy; Habib Badri Ghavifekr; Mohammad Hossein Sedaaghi
Journal:  J Med Signals Sens       Date:  2015 Jul-Sep

4.  A Combinational Clustering Based Method for cDNA Microarray Image Segmentation.

Authors:  Guifang Shao; Tiejun Li; Wangda Zuo; Shunxiang Wu; Tundong Liu
Journal:  PLoS One       Date:  2015-08-04       Impact factor: 3.240

5.  Automatic microarray image segmentation with clustering-based algorithms.

Authors:  Guifang Shao; Dongyao Li; Junfa Zhang; Jianbo Yang; Yali Shangguan
Journal:  PLoS One       Date:  2019-01-22       Impact factor: 3.240

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.