Texture analysis of ultrasound images of livers

Klaus Juel Olsen

It is interesting to compare the results previously obtained and reported in the literature by other research groups and the results in this project. However, one must be very careful when making direct comparisons because many things in the design and analysis may differ.

We have focused on the differentiation between normal liver images and images from livers with diffuse diseases.

For this two group situation the computerized analysis produces hit rates ranging from about 50% to more than 80%. Lerski et al. obtained considerably higher hit rates (83-94%) when differentiating two group situations without mixed cases. However, the statistical treatment of the data must be criticized. The discriminations were neither performed jackknifed nor with calibration and test data set. Furthermore, the reported hit rates seem to be obtained as the maxima of all possible parameter combinations of the eight parameters with highest univariate discriminating capability.

The statistical treatment of the results in Raeth et al. is far better, but one problem is not considered properly. Since they use three images from each liver, the results will be biased, even when they use a jackknifed discrimination. However, the results are good. The overall hit rate, for discriminating between the diffuse diseases fat, hepatitis, cirrhosis/fibrosis and a situation of mixed fat and cirrhosis/fibrosis, is 80%.

Keeping the differences in statistical methods in mind, the results of the computer analysis in the liver project are quite acceptable. The performance in the visual evaluation lies within the range of the reported experiments. The small superiority of the computer analysis (d-type images) as compared to the visual evaluation, is found in this project as well as in other projects (Raeth et al.)

Since the computer analysis of ultrasound images performs at least as well as the visual evaluation of the images, the combination of the two approaches is likely to improve the precision of the diagnoses. However, the calibration problems with the BK1846 scanner influenced the present dataset so it is not adequate for the design of a final system. In the construction of a final system the following quidelines are advisable from the experiences in this project:

IMSOR Ph.D Thesis 51, 1988

Last modified August 18, 1996
Finn Kuno Christensen

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