PuSH - Publikationsserver des Helmholtz Zentrums München

Abmayr, W. ; Abele, L. ; Kugler, J.W. ; Borst, H.

Capabilities of a nonlinear gradient and a thresholding algorithm for the segmentation of Papanicolaou-stained cervical cell.

Analyt. Quant. Cytol. Histol. 2, 221-233 (1980)
Zum Artikel PMC
The first and most important task of automatic high-resolution cell image analysis is the segmentation of the scanned cells. Different methods of cell segmentation have been developed, but a comparison of the capabilities of such algorithms has not been done. This study evaluated 2 different segmentation methods for cell images, namely, a nonlinear gradient algorithm with a subsequent tracing method and a thresholding algorithm based on the information from 3 histograms with a subsequent nonlinear cleaning of the binary thresholded images. The same Papanicolaou-stained cell data base was used in both methods. Automatic segmentation of nucleus and cytoplasm was performed, and a comparison with visually segmented areas of the nucleus and cytoplasm was carried out. The difference between the visual method and the automatic segmentation method by thresholding is discussed in terms of classification results.
Altmetric
Weitere Metriken?
[➜Einloggen]
Zusatzinfos bearbeiten [➜Einloggen]
Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
ISSN (print) / ISBN 0190-0471
Zeitschrift Analytical and Quantitative Cytology and Histology
Quellenangaben Band: 2, Heft: 3, Seiten: 221-233 Artikelnummer: , Supplement: ,
Verlag Science Printers and Publ.
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Translational Metabolic Oncology (IDC-TMO)