19 Multimodal Medical Supervised Image Fusion Method
Abstract
Medical image fusion has become important for the analysis and treatment of diseases because it offers more comprehensive and correct information by combining one-of-a-kind modalities. However, conventional medical image fusion strategies are often be afflicted by obstacles that include lack of spatial and structural data, low evaluation, and trouble in maintaining anatomical features. To overcome these challenges, a new multimodal clinically supervised image fusion method is proposed in this chapter. The proposed method is primarily based on supervised gaining knowledge, where a deep convolutional neural community (DCNN) is used ...
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