| Summary: | 碩士 === 國立成功大學 === 資訊及電子工程研究所 === 82 === Ultrasonic imaging is a popular and non-invasive tool
frequently used in the diagnoses of liver diseases. However,
the ultrasonic imaging condition, including focusing and time-
gain control(TGC), and the heterogeneous textures, such as
blood vessels and hepatic ducts in the acquired echo images,
may confuse the echo texture analysis and induce incorrect
texture measurement. To obtain suitable quality sonogram and
reliable measurement, we have done many experiments for seeking
the best suitable acquisition setting. The sonograms are
acquired from inter-coastal view and the setting of focusing
and TGC is selected and fixed specifically for our ultrasonic
imaging machine. The heterogeneous textures are excluded from
the liver texture measurement by using multiscale edge detector
based on wavelet transform associated with B-spline
interpolation. To improve the accuracy of echo texture
analysis, the blood vessels and hepatic ducts are excluded in
texture analysis. In texture analysis, a new method, called
"Occurrence Probability of Texture Structure," is proposed in
this thesis. The texture measures are computed based on the
surface structure in a small local area. Besides, co-occurrence
matrix, statistical feature matrix, texture spectrum, fractal
dimension descriptor and this method are used to understand and
describe the ultrasonic liver images, too. From all these
texture descriptors, we can obtain 126 texture parameters.
However, not all of these parameters are useful in liver
diagnosis. Thus, we search for the effective classification
parameters by using the forward sequential search algorithm.
The useful parameters are sent into a probabilistic neural
network for the classification of liver diseases. A relative
score is computed to indicate the exacerbation of progressive
liver diseases. The experimental results show that the correct
classification rate is greatly improved in comparison with the
conventional methods without removal of heterogeneous
structures.
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