A neural network architecture for automatic segmentation of fluorescence micrographs

Nattkemper TW, Wersing H, Schubert W, Ritter H (2002)
In: Neurocomputing. NEUROCOMPUTING, 48(1-4). ELSEVIER SCIENCE BV: 357-367.

Konferenzbeitrag | Veröffentlicht | Englisch
 
Download
Es wurde kein Volltext hochgeladen. Nur Publikationsnachweis!
Abstract / Bemerkung
A system for the automatic segmentation of fluorescence micrographs is presented. In the first step, positions of fluorescent cells are detected by a fast learning neural network, which acquires the visual knowledge from a set of training cell-image patches selected by the user. Guided by the detected cell positions the system extracts in the second step the contours of the cells. For contour extraction, a recurrent neural network model is used to approximate the cell shapes. Even though the micrographs are noisy and the fluorescent cells vary in shape and size, the system detects at minimum 95% of the cells. (C) 2002 Elsevier Science B.V. All rights reserved.
Stichworte
segmentation; fluorescence microscopy; contour grouping; proteomics; functional
Erscheinungsjahr
2002
Titel des Konferenzbandes
Neurocomputing
Band
48
Ausgabe
1-4
Seite(n)
357-367
ISSN
0925-2312
Page URI
https://pub.uni-bielefeld.de/record/1613503

Zitieren

Nattkemper TW, Wersing H, Schubert W, Ritter H. A neural network architecture for automatic segmentation of fluorescence micrographs. In: Neurocomputing. NEUROCOMPUTING. Vol 48. ELSEVIER SCIENCE BV; 2002: 357-367.
Nattkemper, T. W., Wersing, H., Schubert, W., & Ritter, H. (2002). A neural network architecture for automatic segmentation of fluorescence micrographs. Neurocomputing, NEUROCOMPUTING, 48, 357-367. ELSEVIER SCIENCE BV. doi:10.1016/S0925-2312(01)00642-7
Nattkemper, T. W., Wersing, H., Schubert, W., and Ritter, H. (2002). “A neural network architecture for automatic segmentation of fluorescence micrographs” in Neurocomputing NEUROCOMPUTING, vol. 48, (ELSEVIER SCIENCE BV), 357-367.
Nattkemper, T.W., et al., 2002. A neural network architecture for automatic segmentation of fluorescence micrographs. In Neurocomputing. NEUROCOMPUTING. no.48 ELSEVIER SCIENCE BV, pp. 357-367.
T.W. Nattkemper, et al., “A neural network architecture for automatic segmentation of fluorescence micrographs”, Neurocomputing, NEUROCOMPUTING, vol. 48, ELSEVIER SCIENCE BV, 2002, pp.357-367.
Nattkemper, T.W., Wersing, H., Schubert, W., Ritter, H.: A neural network architecture for automatic segmentation of fluorescence micrographs. Neurocomputing. NEUROCOMPUTING. 48, p. 357-367. ELSEVIER SCIENCE BV (2002).
Nattkemper, Tim Wilhelm, Wersing, Heiko, Schubert, Walter, and Ritter, Helge. “A neural network architecture for automatic segmentation of fluorescence micrographs”. Neurocomputing. ELSEVIER SCIENCE BV, 2002.Vol. 48. NEUROCOMPUTING. 357-367.