Abstract
Ultrasonic image analysis provides a reliable and noninvasive method for measuring liver histology. This method enables the classification of liver states as normal, hepatitis, or liver cirrhosis. This method involves the definition of suitable settings for the ultrasonic device. Inhomogeneous structures from the area of interest in the image are removed and useful texture parameters are searched from the co-occurrence matrix, statistical feature matrix, texture spectrum, and fractal dimension descriptors, using the forward sequential search method. The selected parameters are then fed into a probabilistic neural network for the classification of liver disease.
Original language | English |
---|---|
Pages (from-to) | 93-101 |
Number of pages | 9 |
Journal | IEEE Engineering in Medicine and Biology Magazine |
Volume | 15 |
Issue number | 6 |
DOIs | |
Publication status | Published - 1996 Nov |
All Science Journal Classification (ASJC) codes
- Biomedical Engineering