Medical images in radiation therapy, especially electronic portal images, are often very poor in quality because of imaging physics. For a reliable patient set-up verification by tracking of relevant features, better in-treatment images are necessary. In this work, we present the prototype of an additive fuzzy system for a locally adaptive image enhancement and a modified associative memory for image restoration. Using a-priori knowledge and the advantages of this hybrid neural-fuzzy system, a much better quality for the in-treatment image can be achieved.
ASJC Scopus subject areas
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering