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6th ESACP Congress, Heidelberg, April 7-11, 1999 |
A110
A polygonization-based method was used to estimate the fractal dimension and
several new scalar lacunarity features from digitized transmission electron
micrographs (TEM) of mouse liver cell nuclei. The fractal features have been
estimated in different segments of 1D curves obtained by scanning the 2D cell
nuclei in a spiral-like fashion called ``peel-off-scanning''. This is a venue
to separate estimates of fractal features in the center and periphery of a
cell nucleus. Our aim was to see if a small set of fractal features could
discriminate between samples from normal (including regenerating) liver,
hyperplastic nodules and hepatocellular carcinomas. The Bhattacharyya
distance was used to evaluate the features on the training data set.
Bayesian classification with pooled covariance matrix and equal prior
probabilties was used as the rule for classification. The conclusion after
testing on an independent test set was that several single fractal features
estimated from the periphery of the cell nuclei could discriminate samples
from the hyperplastic nodules and hepatocellular carcinomas from normal ones.
The outer 25%-30% of the cell nuclei contained important texture information
about the differences between the classes. The polygonization-based method
was also used as an analysis tool to relate the differences between the
classes to differences in the chromatin structure.
DIAGNOSTIC CLASSIFICATION BASED ON FRACTAL FEATURES IN THE PERIPHERY OF CELL
NUCLEI FROM LIVER LESIONS
Nielsen B, Albregtsen F, Danielsen HE
Group for Data Analysis, Signal and Image Processing, Department of
Informatics, University of Oslo Blindern, Oslo,
Division of Digital Pathology, the Norwegian Radium Hospital, Montebello,
Oslo, Norway