7 Soft Computing Approaches to Medical Image Fusion
K. Lakshmi Narayanan, M. Radha, U. Lenin Marksia · 2024
Clinical image fusion is a critical technique in the field of scientific imaging which aims to mix complementary information from multiple images of the same challenge to reap a fused image with more advantageous diagnostic and medical fee. Conventional image fusion strategies have limitations in handling complex and noisy scientific images, which have prompted the use of soft computing strategies for medical image fusion. Gentle computing is an interdisciplinary subject that combines strategies from artificial intelligence, computer science, and statistical strategies to solve complex real global troubles. Gentle computing techniques along with fuzzy logic, genetic algorithms, and synthetic neural networks were carried out accurately in medical image fusion because of their capability to deal with uncertainty and imprecision in medical images. These strategies permit for the fusion of images at special scales, resolutions, and modalities, resulting in a sharper and more informative fused image. For instance, fuzzy logic is used for image fusion by representing pixel depths as fuzzy units and acting fusion based totally on fuzzy operators. Genetic algorithms, alternatively, mimic the herbal selection method to generate high-quality fused images via selecting and mixing the great features from one-of-a-kind input images. Synthetic neural networks have shown exquisite potential in medical image fusion by way of the use of their capacity to research and adapt to complex image records.