A novel image segmentation scheme based on a neural network has been implemented to segment magnetic resonance head images. A three‐layer perceptron‐type neural network, trained with backward error propagation algorithm was used. The scheme utilizes first‐echo intensity and computed T2 values to construct a two‐parameter space for classification. After training on a selected slice, the method successfully segments all slices for a given subject without any further human interaction.
|Number of pages||5|
|Journal||International Journal of Imaging Systems and Technology|
|Publication status||Published - 1992 Jan 1|
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering