Multi-modality is widely used in medical imaging, because it can provide multiinformation
about a target (tumor, organ or tissue). Segmentation using multimodality consists of fusing …

Multimodal medical image fusion consists in combining two or more images of the same or
different modalities aiming to improve the image content, and preserve information. The …

Pixel-level image fusion is designed to combine multiple input images into a fused image,
which is expected to be more informative for human or machine perception as compared to …

Infrared and visible image fusion aims to obtain a synthetic image that can simultaneously
exhibit salient objects and provide abundant texture details. However, existing deep …

Multimodal medical image fusion plays a vital role in different clinical imaging sensor
applications. This paper presents a novel multimodal medical image fusion method that …

Intuitionistic fuzzy set (IFS) is a representative model of fuzzy theory, and it is widely used to
deal with fuzzy and uncertain problems in many practical applications. In IFS theory, the …

This article aims to develop a novel hybrid multi‐attribute group decision‐making approach
under interval‐valued intuitionistic fuzzy sets (IVIFS) by integrating variable weight …

In this work, a new fuzzy logic-based algorithm is proposed for the enhancement of low light
color images. A generalization of a fuzzy set known as an intuitionistic fuzzy set (IFS) is used …

Multimodal medical image fusion is effectuated to minimize the redundancy while
augmenting the necessary information from the input images acquired using different …

The intuitionistic fuzzy set (IFS), as a generation of Zadeh's fuzzy set, can express and
process uncertainty much better. Similarity measures between IFSs are used to indicate the …