Multimodal Medical Image Fusion using Hybrid Domains

In a variety of clinical applications, image fusion is critical for merging data from multiple sources into single, more understandable outcome. The use medical technologies to assist the physician in executing combination procedures can be advantageous. diagnostic process includes preoperative planning, intra operative supervision, an interventional treatment. this thesis, technique was suggested that used model PCA and CNN. A method real-time employs pre-trained neural networks synthesize single several real-time. innovative images created based on deep network feature maps convolution network. Picture has become increasingly popular as result large capturing techniques available. proposed design implemented using learning technique. accuracy around 15% higher than existing design. algorithm verified through simulation experiment different multimodality images. Experimental results are evaluated by number well-known performance evaluation metrics