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      Minimum spanning tree, Voronoi's tesselation and Johnson-Mehl diagrams in human lung carcinoma.

      Pathology, research and practice
      Adenocarcinoma, pathology, Carcinoma, Non-Small-Cell Lung, Carcinoma, Small Cell, Carcinoma, Squamous Cell, Cell Nucleus, DNA, Neoplasm, analysis, Humans, Image Processing, Computer-Assisted, Lung Neoplasms, ultrastructure

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          Abstract

          A program written in Amba was developed for the automated construction of minimum spanning trees, Voronoi's tesselation and Johnson-Mehl diagrams, combined with quantitative measurements of nuclear parameters in histopathological specimens. Sections, 4 microns thick obtained from paraffin-embedded surgical lung specimens, were Feulgen-stained. The boundaries of the nuclei were calculated automatically after interactive identification of the relevant cells. The geometric centres of the nuclei were computed. They were used for constructing the minimum spanning tree, Voronoi's tesselation and the Diriclet cells. The direction of the main axis to the best fitting ellipsis according to the nuclear size was used for construction of the Johnson-Mehl diagrams. The following textural parameters were measured: 1) Minimum spanning tree: Distribution of neighbouring cells; minimum distance between neighbouring cells according to number of neighbours. 2) Voronoi's tesselation: Area and surface of obtained cells; Ratio of nuclear area/cell area. 3) Johnson-Mehl diagram: Area and surface of obtained cells; Ratio of nuclear area/cell area. The following nuclear parameters were measured: 1) Area, surface, absolute extinction (DNA-content); Similarity of quantitative nuclear parameters between neighbouring cells and in relation to number of neighbouring cells was analyzed. Twenty cases of primary lung carcinoma (five cases of each of epidermoid, adeno, large cell anaplastic, and small cell anaplastic carcinoma) were measured. Analysis of texture parameters in combination with morphometric nuclear parameters offers new possibilities in quantitative histopathology.

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