Conference paper
Image segmentation based on scaled fuzzy membership functions
As a basis for an automated interpretation of magnetic resonance images, the authors propose a fuzzy segmentation method. The method uses five standard fuzzy membership functions: small, small medium, medium, large medium, and large. The method fits these membership functions to the modes of interest in the image histogram by means of a piecewise-linear transformation.
A test example is given concerning a human head image, including a sensitivity analysis based on the fuzzy area measure. The method provides a rule-based interface to the physician
| Language: | English |
|---|---|
| Publisher: | IEEE |
| Year: | 1993 |
| Pages: | 714-718 |
| Proceedings: | IEEE International Conference on Fuzzy Systems |
| ISBN: | 0780306147 and 9780780306141 |
| Types: | Conference paper |
| DOI: | 10.1109/FUZZY.1993.327401 |
Area measurement Brain Fuzzy sets Histograms Hospitals Humans Image segmentation Magnetic heads Magnetic resonance NMR image Volume measurement automated image interpretation biomedical NMR fuzzy area measure fuzzy set theory human head image image histogram image segmentation knowledge based systems medical diagnostic computing piecewise-linear transformation rule-based interface scaled fuzzy membership functions sensitivity analysis
