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 conventional approach to machine learning and deep learning approach: an experimental and comprehensive review of image fusion techniques
G Choudhary, D Sethi - Archives of Computational Methods in …, 2023 - Springer
Images captured from a single or multiple imaging sensors with considerable focus or
numerous exposures of the same or different modalities do not provide all relevant …
numerous exposures of the same or different modalities do not provide all relevant …
Parameter adaptive unit-linking pulse coupled neural network based MRI–PET/SPECT image fusion
Medical image fusion has many applications to healthcare that is accomplished by
extracting and then combining the complementary information from multiple medical images …
extracting and then combining the complementary information from multiple medical images …
Multi-focus image fusion techniques: a survey
S Bhat, D Koundal - Artificial Intelligence Review, 2021 - Springer
Abstract Multi-Focus Image Fusion (MFIF) is a method that combines two or more source
images to obtain a single image which is focused, has improved quality and more …
images to obtain a single image which is focused, has improved quality and more …
Brain CT and MRI medical image fusion using convolutional neural networks and a dual-channel spiking cortical model
The aim of medical image fusion is to improve the clinical diagnosis accuracy, so the fused
image is generated by preserving salient features and details of the source images. This …
image is generated by preserving salient features and details of the source images. This …
Depth-distilled multi-focus image fusion
Homogeneous regions, which are smooth areas that lack blur clues to discriminate if they
are focused or non-focused. Therefore, they bring a great challenge to achieve high …
are focused or non-focused. Therefore, they bring a great challenge to achieve high …
CT and MRI medical image fusion using noise-removal and contrast enhancement scheme with convolutional neural network
Medical image fusion (MIF) has received painstaking attention due to its diverse medical
applications in response to accurately diagnosing clinical images. Numerous MIF methods …
applications in response to accurately diagnosing clinical images. Numerous MIF methods …
Fusion PSPnet image segmentation based method for multi-focus image fusion
To address the problem that the traditional multi-focus images fusion methods cannot fully
use of spatial context information. A novel image segmentation method for multi-focus image …
use of spatial context information. A novel image segmentation method for multi-focus image …
Siamese networks and multi-scale local extrema scheme for multimodal brain medical image fusion
Multimodal medical image fusion is an auxiliary approach to help doctors diagnose
diseases accurately leveraging information enhancement technology. Up to now, none of …
diseases accurately leveraging information enhancement technology. Up to now, none of …
Fidelity-driven optimization reconstruction and details preserving guided fusion for multi-modality medical image
K He, X Zhang, D Xu, J Gong… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
By integrating effective features of multi-modality medical images to provide richer
information, multi-modality medical image fusion has been substantially used in computer …
information, multi-modality medical image fusion has been substantially used in computer …