Abstract
We present a novel algorithm for obtaining fuzzy segmentations of images that are subject to multiplicative intensity inhomogeneities, such as magnetic resonance images. The algorithm is formulated by modifying the objective function in the fuzzy c-means algorithm to include a multiplier field, which allows the centroids for each class to vary across the image. First and second order regularization terms ensure that the multiplier field is both slowly varying and smooth. An iterative algorithm that minimizes the objective function is described, and its efficacy is demonstrated on several test images.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 555-563 |
| Number of pages | 9 |
| Journal | Proceedings of SPIE - The International Society for Optical Engineering |
| Volume | 3338 |
| DOIs | |
| State | Published - Dec 1 1998 |
| Event | Medical Imaging 1998: Image Processing - San Diego, CA, United States Duration: Feb 23 1998 → Feb 23 1998 |
Keywords
- Fuzzy c-means
- Image segmentation
- Intensity inhomogeneities
- Magnetic resonance imaging
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering