Multi-focus image fusion: A survey of the state of the art
Multi-focus image fusion is an effective technique to extend the depth-of-field of optical
lenses by creating an all-in-focus image from a set of partially focused images of the same …
lenses by creating an all-in-focus image from a set of partially focused images of the same …
From multi-scale decomposition to non-multi-scale decomposition methods: a comprehensive survey of image fusion techniques and its applications
Image fusion is a well-recognized and a conventional field of image processing. Image
fusion provides an efficient way of enhancing and combining pixel-level data resulting in …
fusion provides an efficient way of enhancing and combining pixel-level data resulting in …
MATR: Multimodal medical image fusion via multiscale adaptive transformer
Owing to the limitations of imaging sensors, it is challenging to obtain a medical image that
simultaneously contains functional metabolic information and structural tissue details …
simultaneously contains functional metabolic information and structural tissue details …
An image quality enhancement scheme employing adolescent identity search algorithm in the NSST domain for multimodal medical image fusion
The fast-developing Image fusion technique has become a necessary one in every field.
Analyzing the efficiency of various fusion technologies analytically and objectively are …
Analyzing the efficiency of various fusion technologies analytically and objectively are …
Novel healthcare framework for cardiac arrest with the application of AI using ANN
Cardiovascular illnesses are the leading cause of mortality worldwide, killing an estimated
27.9 million people each year, accounting for 31% of fatalities worldwide. Cardiovascular …
27.9 million people each year, accounting for 31% of fatalities worldwide. Cardiovascular …
Structure tensor and nonsubsampled shearlet transform based algorithm for CT and MRI image fusion
X Liu, W Mei, H Du - Neurocomputing, 2017 - Elsevier
Multimodal medical image fusion technique contributes to the reduction of information
uncertainty and improves the clinical diagnosis accuracy, the aim of which is to preserve …
uncertainty and improves the clinical diagnosis accuracy, the aim of which is to preserve …
Nonsubsampled shearlet based CT and MR medical image fusion using biologically inspired spiking neural network
This paper presents a new fusion scheme for the CT and MR medical images that utilizes
both the features of the nonsubsampled shearlet transform (NSST) and spiking neural …
both the features of the nonsubsampled shearlet transform (NSST) and spiking neural …
Multi-modal medical image fusion framework using co-occurrence filter and local extrema in NSST domain
The fusion of vital imaging information has turned into a primary issue for biomedical
applications. In this paper, a new multi-modality medical image fusion method is proposed in …
applications. In this paper, a new multi-modality medical image fusion method is proposed in …
Multi-modality medical image fusion based on image decomposition framework and nonsubsampled shearlet transform
X Liu, W Mei, H Du - Biomedical Signal Processing and Control, 2018 - Elsevier
Medical image fusion increases accuracy of clinical diagnosis and analysis through
integrating complementary information of multi-modality medical images. A novel multi …
integrating complementary information of multi-modality medical images. A novel multi …
EGGDD: An explicit dependency model for multi-modal medical image fusion in shift-invariant shearlet transform domain
Most of the traditional medical image fusion methods that use the multi-scale decomposition
schemes suffer from the bad image representations and the loss of the dependency in …
schemes suffer from the bad image representations and the loss of the dependency in …