A way toward analyzing high-content bioimage data by means of semantic annotation and visual data mining

Progress in Biomedical Optics and Imaging - Proceedings of SPIE

Volumn 7259, Issue , 2009, Pages

  Herold, Julia ^a   Abouna, Sylvie ^b   Zhou, Luxian ^b   Pelengaris, Stella ^b   Epstein, David B A ^b   Khan, Michael ^b   Nattkemper, Tim W ^a  

^a BIELEFELD UNIVERSITY   (Germany)

^b UNIVERSITY OF WARWICK   (United Kingdom)

Author keywords

Diabetes; High content imaging; Machine learning; Multichannel; Semantic annotation; Visual data mining

Indexed keywords

HIGH-CONTENT; IMAGING MACHINES; MULTI-CHANNEL; SEMANTIC ANNOTATIONS; VISUAL DATA MINING;

DRUG THERAPY; EDUCATION; IMAGE ANALYSIS; IMAGING SYSTEMS; ROBOT LEARNING; SEMANTICS;

MEDICAL IMAGING;

EID: 71649091932     PISSN: 16057422     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.811710     Document Type: Conference Paper

References (13)

1. Starkuviene, V. and Pepperkok, R., "The potential of high-content high-throughput microscopy in drug discovery," Br J Pharmacol 152, 62-71 (2007).
2. Zimmermann, T., Rietdorf, J., and Pepperkok, R., "Spectral imaging and its applications in live cell microscopy,quot; FEBS Lett 546, 87-92 (2003).
3. Schubert, W., Bonnekoh, B., Pommer, A., Philipsen, L., Bckelmann, R., Malykh, Y., Gollnick, H., Friedenberger, M., Bode, M., and Dress, A., "Analyzing proteome topology and function by automated multidimensional fluorescence microscopy.," Nat Biotechnol 24, 1270-1278 (2006).
4. Levenson, R. and Hoyt, C., "Spectral imaging and microscopy," Am. Lab. 32, 26-33 (2000).
5. Keim, D., "Information visualization and visual data mining," IEEE Trans Vis Comput Graphics 8(1), 1-8 (2002).
6. Vapnik, V., [The Nature of Statistical Learning Theory], Springer Verlag New York, New York (1996).
7. Tomasi, C. and Manduchi, R., "Bilateral filtering for gray and color images,"ICCV, 839-46 (1998).
8. Herold, J., Friedenberger, M., Bode, M., Rajpoot, N., Schubert, W., and Nattkemper, T., "Flexible synapse detection in fluorescence micrographs by modeling human expert grading,"Proc. of 2008 IEEE International Symposium on Biomedical Imaging (ISBI), 1347-1350 (2008).
9. Pearson, K., "On lines and planes of closest fit to a system of point in space," Philosophical Magazin 2, 559-572 (1901).
10. Hanley, J., "Reciever operating characteristic mehtodology: the state of the art," Crit. Rev. in Diagn. Imaging 29, 307-35 (1989).
11. Gonzalez, R. and Woods, R., [Digital Image Processing (2nd Edition)], Prentice Hall, New Jersey (2002).
12. Otsu, N., "A threshold selection method from gray-level histograms," IEEE Trans Syst Man Cybern 9, 62-66 (1979).
13. Martinetz, T. and Schulten, K., "A neural gas network learns topology," IEEE International Conference on Artificial Neural Networks 1, 397-407 (1991).