A review on multimodal medical image fusion: Compendious analysis of medical modalities, multimodal databases, fusion techniques and quality metrics
Background and objectives Over the past two decades, medical imaging has been
extensively apply to diagnose diseases. Medical experts continue to have difficulties for …
extensively apply to diagnose diseases. Medical experts continue to have difficulties for …
Multimodal medical image fusion review: Theoretical background and recent advances
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 …
different modalities aiming to improve the image content, and preserve information. The …
Medical image fusion with parameter-adaptive pulse coupled neural network in nonsubsampled shearlet transform domain
As an effective way to integrate the information contained in multiple medical images with
different modalities, medical image fusion has emerged as a powerful technique in various …
different modalities, medical image fusion has emerged as a powerful technique in various …
A medical image fusion method based on convolutional neural networks
Medical image fusion technique plays an an increasingly critical role in many clinical
applications by deriving the complementary information from medical images with different …
applications by deriving the complementary information from medical images with different …
Medical image fusion: A survey of the state of the art
AP James, BV Dasarathy - Information fusion, 2014 - Elsevier
Medical image fusion is the process of registering and combining multiple images from
single or multiple imaging modalities to improve the imaging quality and reduce …
single or multiple imaging modalities to improve the imaging quality and reduce …
Unsupervised deep image fusion with structure tensor representations
Convolutional neural networks (CNNs) have facilitated substantial progress on various
problems in computer vision and image processing. However, applying them to image …
problems in computer vision and image processing. However, applying them to image …
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 …
Anatomical-functional image fusion by information of interest in local Laplacian filtering domain
J Du, W Li, B Xiao - IEEE Transactions on Image Processing, 2017 - ieeexplore.ieee.org
A novel method for performing anatomical magnetic resonance imaging-functional (positron
emission tomography or single photon emission computed tomography) image fusion is …
emission tomography or single photon emission computed tomography) image fusion is …
A fusion algorithm for infrared and visible images based on adaptive dual-channel unit-linking PCNN in NSCT domain
In this paper, a novel fusion algorithm based on the adaptive dual-channel unit-linking pulse
coupled neural network (PCNN) for infrared and visible images fusion in nonsubsampled …
coupled neural network (PCNN) for infrared and visible images fusion in nonsubsampled …
Gesenet: A general semantic-guided network with couple mask ensemble for medical image fusion
At present, multimodal medical image fusion technology has become an essential means for
researchers and doctors to predict diseases and study pathology. Nevertheless, how to …
researchers and doctors to predict diseases and study pathology. Nevertheless, how to …