Analytical Cellular Pathology

Analytical Cellular Pathology / 1999 / Article

Open Access

Volume 18 |Article ID 757849 |

Christophe Boudry, Paulette Herlin, Benoit Plancoulaine, Eric Masson, Abderrahim Elmoataz, Hubert Cardot, Michel Coster, Daniel Bloyet, Jean‐Louis Chermant, "Automatic Morphological Sieving: Comparison between Different Methods, Application to DNA Ploidy Measurements", Analytical Cellular Pathology, vol. 18, Article ID 757849, 8 pages, 1999.

Automatic Morphological Sieving: Comparison between Different Methods, Application to DNA Ploidy Measurements

Received06 Jul 1998
Accepted02 Jul 1999


The aim of the present study is to propose alternative automatic methods to time consuming interactive sorting of elements for DNA ploidy measurements. One archival brain tumour and two archival breast carcinoma were studied, corresponding to 7120 elements (3764 nuclei, 3356 debris and aggregates). Three automatic classification methods were tested to eliminate debris and aggregates from DNA ploidy measurements (mathematical morphology (MM), multiparametric analysis (MA) and neural network (NN)). Performances were evaluated by reference to interactive sorting. The results obtained for the three methods concerning the percentage of debris and aggregates automatically removed reach 63, 75 and 85% for MM, MA and NN methods, respectively, with false positive rates of 6, 21 and 25%. Information about DNA ploidy abnormalities were globally preserved after automatic elimination of debris and aggregates by MM and MA methods as opposed to NN method, showing that automatic classification methods can offer alternatives to tedious interactive elimination of debris and aggregates, for DNA ploidy measurements of archival tumours.

Copyright © 1999 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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