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Conference Paper: Segmentation-based retrospective shading correction in fluorescence microscopy E. coli images for quantitative analysis

TitleSegmentation-based retrospective shading correction in fluorescence microscopy E. coli images for quantitative analysis
Authors
KeywordsFluorescence microscopy E. Coli image
Segmentation
Shading correction
Issue Date2009
PublisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://spie.org/x1848.xml
Citation
The 6th International Symposium on Multispectral Image Processing and Pattern Recognition, Yichang, China, 30 October-1 November 2009. In Proceedings of SPIE, 2009, v. 7498, p. 749830:1-749830:8 How to Cite?
AbstractDue to the inherent imperfections in the imaging process, fluorescence microscopy images often suffer from spurious intensity variations, which is usually referred to as intensity inhomogeneity, intensity non uniformity, shading or bias field. In this paper, a retrospective shading correction method for fluorescence microscopy Escherichia coli (E. Coli) images is proposed based on segmentation result. Segmentation and shading correction are coupled together, so we iteratively correct the shading effects based on segmentation result and refine the segmentation by segmenting the image after shading correction. A fluorescence microscopy E. Coli image can be segmented (based on its intensity value) into two classes: the background and the cells, where the intensity variation within each class is close to zero if there is no shading. Therefore, we make use of this characteristics to correct the shading in each iteration. Shading is mathematically modeled as a multiplicative component and an additive noise component. The additive component is removed by a denoising process, and the multiplicative component is estimated using a fast algorithm to minimize the intra-class intensity variation. We tested our method on synthetic images and real fluorescence E.coli images. It works well not only for visual inspection, but also for numerical evaluation. Our proposed method should be useful for further quantitative analysis especially for protein expression value comparison. © 2009 Copyright SPIE - The International Society for Optical Engineering.
Persistent Identifierhttp://hdl.handle.net/10722/126197
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorMai, Fen_HK
dc.contributor.authorChang, Cen_HK
dc.contributor.authorLiu, Wen_HK
dc.contributor.authorXu, Wen_HK
dc.contributor.authorHung, YSen_HK
dc.date.accessioned2010-10-31T12:15:03Z-
dc.date.available2010-10-31T12:15:03Z-
dc.date.issued2009en_HK
dc.identifier.citationThe 6th International Symposium on Multispectral Image Processing and Pattern Recognition, Yichang, China, 30 October-1 November 2009. In Proceedings of SPIE, 2009, v. 7498, p. 749830:1-749830:8en_HK
dc.identifier.issn0277-786Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/126197-
dc.description.abstractDue to the inherent imperfections in the imaging process, fluorescence microscopy images often suffer from spurious intensity variations, which is usually referred to as intensity inhomogeneity, intensity non uniformity, shading or bias field. In this paper, a retrospective shading correction method for fluorescence microscopy Escherichia coli (E. Coli) images is proposed based on segmentation result. Segmentation and shading correction are coupled together, so we iteratively correct the shading effects based on segmentation result and refine the segmentation by segmenting the image after shading correction. A fluorescence microscopy E. Coli image can be segmented (based on its intensity value) into two classes: the background and the cells, where the intensity variation within each class is close to zero if there is no shading. Therefore, we make use of this characteristics to correct the shading in each iteration. Shading is mathematically modeled as a multiplicative component and an additive noise component. The additive component is removed by a denoising process, and the multiplicative component is estimated using a fast algorithm to minimize the intra-class intensity variation. We tested our method on synthetic images and real fluorescence E.coli images. It works well not only for visual inspection, but also for numerical evaluation. Our proposed method should be useful for further quantitative analysis especially for protein expression value comparison. © 2009 Copyright SPIE - The International Society for Optical Engineering.en_HK
dc.languageengen_HK
dc.publisherS P I E - International Society for Optical Engineering. The Journal's web site is located at http://spie.org/x1848.xmlen_HK
dc.relation.ispartofProceedings of SPIE - The International Society for Optical Engineeringen_HK
dc.subjectFluorescence microscopy E. Coli imageen_HK
dc.subjectSegmentationen_HK
dc.subjectShading correctionen_HK
dc.titleSegmentation-based retrospective shading correction in fluorescence microscopy E. coli images for quantitative analysisen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1996-756X&volume=7498&spage=74983O:1&epage=749830:8&date=2009&atitle=Segmentation-based+retrospective+shading+correction+in+fluorescence+microscopy+E.+coli+images+for+quantitative+analysis-
dc.identifier.emailChang, C: cqchang@eee.hku.hken_HK
dc.identifier.emailXu, W: wcxu@eee.hku.hken_HK
dc.identifier.emailHung, YS: yshung@hkucc.hku.hken_HK
dc.identifier.authorityChang, C=rp00095en_HK
dc.identifier.authorityXu, W=rp00198en_HK
dc.identifier.authorityHung, YS=rp00220en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1117/12.847036en_HK
dc.identifier.scopuseid_2-s2.0-71649098567en_HK
dc.identifier.hkuros173441en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-71649098567&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume7498en_HK
dc.identifier.spage74983O:1en_HK
dc.identifier.epage749830:8en_HK
dc.publisher.placeUnited Statesen_HK
dc.description.otherThe 6th International Symposium on Multispectral Image Processing and Pattern Recognition, Yichang, China, 30 October-1 November 2009. In Proceedings of SPIE, 2009, v. 7498, p. 749830:1-749830:8-
dc.identifier.scopusauthoridMai, F=12804393400en_HK
dc.identifier.scopusauthoridChang, C=7407033052en_HK
dc.identifier.scopusauthoridLiu, W=7407341280en_HK
dc.identifier.scopusauthoridXu, W=7404428876en_HK
dc.identifier.scopusauthoridHung, YS=8091656200en_HK

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