期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2018
卷号：9
期号：2
页码：72-81
语种：English
出版社：Ayushmaan Technologies
摘要：Medical image fusion is important in biomedical applications for non-invasive diagnosis. Image fusion aims to reduce defects associated with single images created from different modalities. These defects make the single-image result less informative and therefore less useful for medical diagnosis. An ideal fused image, created from two or more multimodality images, increases the accuracy, information content and improves visual properties. Current state-of-the-art image fusion techniques have not successfully resolved the poor visual properties, leading to lessthan-ideal information quality. This paper describes a novel technique to improve information quality of fused images, with many practical applications in the biomedical, military, and remote sensing. The proposed algorithm combines the action of Gabor filtering, maximum pixel intensity selection and Pulse Coupled Neural Network (PCNN) implementation. The results are then used to create a fused image. As a proof of concept, several images are evaluated with standard criteria and compared with results from existing image fusion methods.
