Integrating semantic annotation and information visualization for the analysis of multichannel fluorescence micrographs from pancreatic tissue

Herold J, Zhou L, Abouna S, Pelengaris S, Epstein D, Khan M, Nattkemper TW (2010)
Computerized Medical Imaging and Graphics 34(6): 446-452.

Download
Es wurde kein Volltext hochgeladen. Nur Publikationsnachweis!
Zeitschriftenaufsatz | Veröffentlicht | Englisch
Autor
; ; ; ; ; ;
Abstract / Bemerkung
The challenging problem of computational bioimage analysis receives growing attention from life sciences. Fluorescence microscopy is capable of simultaneously visualizing multiple molecules by staining with different fluorescent dyes. In the analysis of the result multichannel images, segmentation of ROIs resembles only a first step which must be followed by a second step towards the analysis of the ROI's signals in the different channels. In this paper we present a system that combines image segmentation and information visualization principles for an integrated analysis of fluorescence micrographs of tissue samples. The analysis aims at the detection and annotation of cells of the Islets of Langerhans and the whole pancreas, which is of great importance in diabetes studies and in the search for new anti-diabetes treatments. The system operates with two modules. The automatic annotation module applies supervised machine learning for cell detection and segmentation. The second information visualization module can be used for an interactive classification and visualization of cell types following the link-and-brush principle for filtering. We can compare the results obtained with our system with results obtained manually by an expert, who evaluated a set of example images three times to account for his intra-observer variance. The comparison shows that using our system the images can be evaluated with high accuracy which allows a considerable speed up of the time-consuming evaluation process. (C) 2009 Elsevier Ltd. All rights reserved.
Erscheinungsjahr
Zeitschriftentitel
Computerized Medical Imaging and Graphics
Band
34
Zeitschriftennummer
6
Seite
446-452
ISSN
PUB-ID

Zitieren

Herold J, Zhou L, Abouna S, et al. Integrating semantic annotation and information visualization for the analysis of multichannel fluorescence micrographs from pancreatic tissue. Computerized Medical Imaging and Graphics. 2010;34(6):446-452.
Herold, J., Zhou, L., Abouna, S., Pelengaris, S., Epstein, D., Khan, M., & Nattkemper, T. W. (2010). Integrating semantic annotation and information visualization for the analysis of multichannel fluorescence micrographs from pancreatic tissue. Computerized Medical Imaging and Graphics, 34(6), 446-452. doi:10.1016/j.compmedimag.2009.10.004
Herold, J., Zhou, L., Abouna, S., Pelengaris, S., Epstein, D., Khan, M., and Nattkemper, T. W. (2010). Integrating semantic annotation and information visualization for the analysis of multichannel fluorescence micrographs from pancreatic tissue. Computerized Medical Imaging and Graphics 34, 446-452.
Herold, J., et al., 2010. Integrating semantic annotation and information visualization for the analysis of multichannel fluorescence micrographs from pancreatic tissue. Computerized Medical Imaging and Graphics, 34(6), p 446-452.
J. Herold, et al., “Integrating semantic annotation and information visualization for the analysis of multichannel fluorescence micrographs from pancreatic tissue”, Computerized Medical Imaging and Graphics, vol. 34, 2010, pp. 446-452.
Herold, J., Zhou, L., Abouna, S., Pelengaris, S., Epstein, D., Khan, M., Nattkemper, T.W.: Integrating semantic annotation and information visualization for the analysis of multichannel fluorescence micrographs from pancreatic tissue. Computerized Medical Imaging and Graphics. 34, 446-452 (2010).
Herold, Julia, Zhou, Luxian, Abouna, Sylvie, Pelengaris, Stella, Epstein, David, Khan, Michael, and Nattkemper, Tim Wilhelm. “Integrating semantic annotation and information visualization for the analysis of multichannel fluorescence micrographs from pancreatic tissue”. Computerized Medical Imaging and Graphics 34.6 (2010): 446-452.

2 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

RAMTaB: robust alignment of multi-tag bioimages.
Raza SE, Humayun A, Abouna S, Nattkemper TW, Epstein DB, Khan M, Rajpoot NM., PLoS One 7(2), 2012
PMID: 22363510
Re-expression of IGF-II is important for beta cell regeneration in adult mice.
Zhou L, Pelengaris S, Abouna S, Young J, Epstein D, Herold J, Nattkemper TW, Nakhai H, Khan M., PLoS One 7(9), 2012
PMID: 22970135

14 References

Daten bereitgestellt von Europe PubMed Central.

The potential of high-content high-throughput microscopy in drug discovery.
Starkuviene V, Pepperkok R., Br. J. Pharmacol. 152(1), 2007
PMID: 17603554
Imaging in systems biology.
Megason SG, Fraser SE., Cell 130(5), 2007
PMID: 17803903
Multidimensional drug profiling by automated microscopy.
Perlman ZE, Slack MD, Feng Y, Mitchison TJ, Wu LF, Altschuler SJ., Science 306(5699), 2004
PMID: 15539606
Decreased beta-cell proliferation impairs the adaptation to pregnancy in rats malnourished during perinatal life.
Avril I, Blondeau B, Duchene B, Czernichow P, Breant B., J. Endocrinol. 174(2), 2002
PMID: 12176660

Gonzalez, 2002
Bilateral filtering for gray and color images
Tomasi, 1998
A machine learning based system for multichannel fluorescence analysis in pancreatic tissue bioimages
Herold, 2008

Bishop, 1996
Receiver operating characteristic (ROC) methodology: the state of the art.
Hanley JA., Crit Rev Diagn Imaging 29(3), 1989
PMID: 2667567
A threshold selection method from gray-level histograms
Otsu, IEEE Trans Syst Man Cybern 9(), 1979

Ware, 2004

Spence, 2006
A way towards analyzing high-content bioimage data by means of semantic annotation and visual data mining
Herold, 2009

Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Web of Science

Dieser Datensatz im Web of Science®

Quellen

PMID: 19969439
PubMed | Europe PMC

Suchen in

Google Scholar