%0 Journal Article %1 boudry_automatic_1999 %A Boudry, C %A Herlin, P %A Plancoulaine, B %A Masson, E %A Elmoataz, A %A Cardot, H %A Coster, M %A Bloyet, D %A Chermant, J.L %D 1999 %J Analytical Cellular Pathology %K imported %N 4 %P 203--210 %T Automatic morphological sieving: comparison between different methods, application to DNA ploidy measurements %U http://www.ncbi.nlm.nih.gov/pubmed/10609564 %V 18 %X 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.

@article{boudry_automatic_1999, abstract = {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.}, added-at = {2011-03-24T16:45:37.000+0100}, author = {Boudry, C and Herlin, P and Plancoulaine, B and Masson, E and Elmoataz, A and Cardot, H and Coster, M and Bloyet, D and Chermant, {J.L}}, biburl = {https://www.bibsonomy.org/bibtex/28cd46ff4243575b0e64faf751da0a1c3/boudry}, interhash = {692fc811f4c05d35200772cae259add0}, intrahash = {8cd46ff4243575b0e64faf751da0a1c3}, issn = {0921-8912}, journal = {Analytical Cellular Pathology}, keywords = {imported}, note = {{PMID:} 10609564}, number = 4, pages = {203--210}, shorttitle = {Automatic morphological sieving}, timestamp = {2011-03-24T16:45:37.000+0100}, title = {Automatic morphological sieving: comparison between different methods, application to {DNA} ploidy measurements}, url = {http://www.ncbi.nlm.nih.gov/pubmed/10609564}, volume = 18, year = 1999 }