Additive fuzzy enhancement and an associative memory for feature tracking in radiation therapy images

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