Morphological image denoising and random-walks spot detection in microarry images

A. Mastrogianni, E. Dermatas, A. Bezerianos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, a novel method for noise reduction and spot detection in microarray images, based on mathematical morphology and Random-Walks model is presented and evaluated. Initially, an automatic method detects the subarrays and a morphological denoising method is used to reduce artifacts at each individual subarray. In the enhanced images, a novel segmentation algorithm based on Random-Walker algorithm (RWA) derives the spot positions. The proposed method is validated in two different databases of real distorted microarray images, giving quite satisfying results both in noise elimination and spot detection accuracy.

Original languageEnglish (US)
Title of host publicationProceedings of the 9th International Workshop on Mathematical Methods in Scattering Theory and Biomedical Engineering: Advanced Topics in Scattering and Biomedical Engineering
PublisherWorld Scientific Publishing Co. Pte Ltd
Pages143-150
Number of pages8
ISBN (Print)9814322024, 9789814322027
StatePublished - 2010
Externally publishedYes
Event2009 9th International Workshop on Mathematical Methods in Scattering Theory and Biomedical Engineering - Patras, Greece
Duration: Oct 9 2009Oct 11 2009

Other

Other2009 9th International Workshop on Mathematical Methods in Scattering Theory and Biomedical Engineering
CountryGreece
CityPatras
Period10/9/0910/11/09

Fingerprint

Image denoising
Image Denoising
Microarrays
Random walk
Mathematical morphology
Noise abatement
Microarray
Mathematical Morphology
Noise Reduction
Denoising
Elimination
Segmentation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Applied Mathematics

Cite this

Mastrogianni, A., Dermatas, E., & Bezerianos, A. (2010). Morphological image denoising and random-walks spot detection in microarry images. In Proceedings of the 9th International Workshop on Mathematical Methods in Scattering Theory and Biomedical Engineering: Advanced Topics in Scattering and Biomedical Engineering (pp. 143-150). World Scientific Publishing Co. Pte Ltd.

Morphological image denoising and random-walks spot detection in microarry images. / Mastrogianni, A.; Dermatas, E.; Bezerianos, A.

Proceedings of the 9th International Workshop on Mathematical Methods in Scattering Theory and Biomedical Engineering: Advanced Topics in Scattering and Biomedical Engineering. World Scientific Publishing Co. Pte Ltd, 2010. p. 143-150.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Mastrogianni, A, Dermatas, E & Bezerianos, A 2010, Morphological image denoising and random-walks spot detection in microarry images. in Proceedings of the 9th International Workshop on Mathematical Methods in Scattering Theory and Biomedical Engineering: Advanced Topics in Scattering and Biomedical Engineering. World Scientific Publishing Co. Pte Ltd, pp. 143-150, 2009 9th International Workshop on Mathematical Methods in Scattering Theory and Biomedical Engineering, Patras, Greece, 10/9/09.
Mastrogianni A, Dermatas E, Bezerianos A. Morphological image denoising and random-walks spot detection in microarry images. In Proceedings of the 9th International Workshop on Mathematical Methods in Scattering Theory and Biomedical Engineering: Advanced Topics in Scattering and Biomedical Engineering. World Scientific Publishing Co. Pte Ltd. 2010. p. 143-150
Mastrogianni, A. ; Dermatas, E. ; Bezerianos, A. / Morphological image denoising and random-walks spot detection in microarry images. Proceedings of the 9th International Workshop on Mathematical Methods in Scattering Theory and Biomedical Engineering: Advanced Topics in Scattering and Biomedical Engineering. World Scientific Publishing Co. Pte Ltd, 2010. pp. 143-150
@inproceedings{5c54a955e6cd4cec9fea260641077032,
title = "Morphological image denoising and random-walks spot detection in microarry images",
abstract = "In this paper, a novel method for noise reduction and spot detection in microarray images, based on mathematical morphology and Random-Walks model is presented and evaluated. Initially, an automatic method detects the subarrays and a morphological denoising method is used to reduce artifacts at each individual subarray. In the enhanced images, a novel segmentation algorithm based on Random-Walker algorithm (RWA) derives the spot positions. The proposed method is validated in two different databases of real distorted microarray images, giving quite satisfying results both in noise elimination and spot detection accuracy.",
author = "A. Mastrogianni and E. Dermatas and A. Bezerianos",
year = "2010",
language = "English (US)",
isbn = "9814322024",
pages = "143--150",
booktitle = "Proceedings of the 9th International Workshop on Mathematical Methods in Scattering Theory and Biomedical Engineering: Advanced Topics in Scattering and Biomedical Engineering",
publisher = "World Scientific Publishing Co. Pte Ltd",

}

TY - GEN

T1 - Morphological image denoising and random-walks spot detection in microarry images

AU - Mastrogianni, A.

AU - Dermatas, E.

AU - Bezerianos, A.

PY - 2010

Y1 - 2010

N2 - In this paper, a novel method for noise reduction and spot detection in microarray images, based on mathematical morphology and Random-Walks model is presented and evaluated. Initially, an automatic method detects the subarrays and a morphological denoising method is used to reduce artifacts at each individual subarray. In the enhanced images, a novel segmentation algorithm based on Random-Walker algorithm (RWA) derives the spot positions. The proposed method is validated in two different databases of real distorted microarray images, giving quite satisfying results both in noise elimination and spot detection accuracy.

AB - In this paper, a novel method for noise reduction and spot detection in microarray images, based on mathematical morphology and Random-Walks model is presented and evaluated. Initially, an automatic method detects the subarrays and a morphological denoising method is used to reduce artifacts at each individual subarray. In the enhanced images, a novel segmentation algorithm based on Random-Walker algorithm (RWA) derives the spot positions. The proposed method is validated in two different databases of real distorted microarray images, giving quite satisfying results both in noise elimination and spot detection accuracy.

UR - http://www.scopus.com/inward/record.url?scp=84903835188&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84903835188&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84903835188

SN - 9814322024

SN - 9789814322027

SP - 143

EP - 150

BT - Proceedings of the 9th International Workshop on Mathematical Methods in Scattering Theory and Biomedical Engineering: Advanced Topics in Scattering and Biomedical Engineering

PB - World Scientific Publishing Co. Pte Ltd

ER -