Computer aided fusion of multi-modality medical images provides a very promising diagnostic tool with numerous clinical applications. The objective of this paper is to present an overview of medical imaging fusion techniques with an emphasis on the use of neural network algorithms. Case studies derived from oncology (data level fusion), microscopy and ultrasound imaging (feature level and decision level fusion), and lesion placement in pallidotomy (data level fusion) are presented. It is anticipated that these tools will help the physician towards a more realistic and quantitative, assessment of disease.