The image fusion methods based on deep learning has become a research hotspot in the
field of computer vision in recent years. This paper reviews these methods from five aspects …

Medical image fusion is a relevant area with widespread application in disease diagnosis
and prediction with easily available image scans of Computed Tomography, Positron …

Medical image fusion has brought practical applications in clinical diagnosis. However,
image fusion methods still face challenges because of problems with the quality of the input …

Automatic pulmonary nodule detection is the most crucial technology in early diagnosis of
lung cancer and early treatment. However, the various nodule type, shape and size …

Medical image fusion is the process of combining information from multiple medical images
of the same body region acquired using different imaging modalities, such as computed …

This paper presents a multimodal image fusion method using a novel decomposition model
based on coupled dictionary learning. The proposed method is general and can be used for …

The synthesis of medical images plays a pivotal role in image-based disease diagnosis. In
recent years, numerous medical image synthesis methods have been proposed …

In this work, VoteDroid a novel fine-tuned deep learning models-based ensemble voting
classifier has been proposed for detecting malicious behavior in Android applications. To …

Multimodal medical image fusion has been attracting the attention of researchers in recent
years because it supports doctors in enhancing clinical diagnosis. Improving the quality of …

Medical image fusion is a technique of extracting information from multiple image modalities
and combining them to create a single image with the aim of improving the image content …